Abstract to the IPOG-F Paper

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This page is an abstract to the paper ``Refining the In-Parameter-Order Strategy for Constructing Covering Arrays'' by M. Forbes, J. Lawrence, Y. Lei, R. N. Kacker and D.R. Kuhn.

Abstract

Covering arrays are structures for well-representing extremely large input spaces and are used to efficiently implement black-box testing for software and hardware. This paper proposes refinements over the In-Parameter-Order strategy (for arbitrary t). When constructing homogeneous-alphabet covering arrays, these refinements reduce runtime in nearly all cases by a factor of more than 5 and in some cases by factors as large as 280. This trend is increasing with the number of columns in the covering array. Moreover, the resulting covering arrays are about 5% smaller. Consequently, this new algorithm has constructed many covering arrays that are the smallest in the literature. A heuristic variant of the algorithm sometimes produces comparably sized covering arrays while running significantly faster.

References

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  2. Charlie J. Colbourn, Covering array tables, Accessed on July 2, 2007.

  3. Donald E. Knuth, The art of computer programming, vol. 4, ch. 7.2.1.3, Addison-Wesley, 2005.

  4. D. R. Kuhn and M. J. Reilly, An investigation of the applicability of design of experiments to software testing, Proceedings of the 27th NASA/IEEE Software Engineering Workshop, NASA Goddard Space Flight Center, December 2002.

  5. Yu Lei, Raghu Kacker, D. Richard Kuhn, Vadim Okun, and James Lawrence, 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 (Washington, DC, USA), IEEE Computer Society, 2007, pp. 549-556.

  6. Y. Lei and K. C. Tai, In-parameter-order: a test generation strategy for pairwise testing, Proceedings of the Third IEEE International Conference on High-Assurance Systems Engineering Symposium, 1998, pp.254-261.

  7. K. C. Tai and Y. Lei, A test generation strategy for pairwise testing, IEEE Transactions on Software Engineering 28 (2002), no. 1, 109-111.


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Last Updated: 2008-01-30

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