Largest induced subgraphs of the n-cube that contain no. 4-cycles
Journal of Combinatorial Theory Series B
The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
A Test Generation Strategy for Pairwise Testing
IEEE Transactions on Software Engineering
Designs, Codes and Cryptography
Constraint Models for the Covering Test Problem
Constraints
Roux-type constructions for covering arrays of strengths three and four
Designs, Codes and Cryptography
IPOG: A General Strategy for T-Way Software Testing
ECBS '07 Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
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
ICSTW '09 Proceedings of the IEEE International Conference on Software Testing, Verification, and Validation Workshops
Binary Covering Arrays and Existentially Closed Graphs
IWCC '09 Proceedings of the 2nd International Workshop on Coding and Cryptology
Iterative exhaustive pattern generation for logic testing
IBM Journal of Research and Development
Upper bounds for covering arrays by tabu search
Discrete Applied Mathematics
Covering arrays from cyclotomy
Designs, Codes and Cryptography
Covering and radius-covering arrays: Constructions and classification
Discrete Applied Mathematics
Randomized post-optimization for t-restrictions
Information Theory, Combinatorics, and Search Theory
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The construction of covering arrays with the fewest rows remains a challenging problem. Most computational and recursive constructions result in extensive repetition of coverage. While some is necessary, some is not. By reducing the repeated coverage, metaheuristic search techniques typically outperform simpler computational methods, but they have been applied in a limited set of cases. Time constraints often prevent them from finding an array of competitive size. We examine a different approach. Having used a simple computation or construction to find a covering array, we employ a post-optimization technique that repeatedly adjusts the array in an attempt to reduce its number of rows. At every stage the array retains full coverage. We demonstrate its value on a collection of previously best known arrays by eliminating, in some cases, 10% of their rows. In the well-studied case of strength two with twenty factors having ten values each, post-optimization produces a covering array with only 162 rows, improving on a wide variety of computational and combinatorial methods. We identify certain important features of covering arrays for which post-optimization is successful.