Multi-Run Tests Based on Background Changing

  • Ireneusz Mrozek


The chapter deals with multi-run tests based on background changing. First, dissimilarity measures for binary vectors are discussed. Then, the optimal (in terms of Pattern Sensitive Fault detection) algorithms with a restricted number of vectors are given. The algorithms are proposed for tests consisting of two, three, and four test vectors. All algorithms are deeply analyzed and their efficiency is analytically proven. Finally, the effective test pattern generation algorithm for tests with a number of test patterns greater than four is provided.


  1. 16.
    Chen, T. Y., Leung, H., and Mak, I. K. Adaptive random testing. In Proceedings of the 9 th Asian Computing Science Conference” (2004), ASIAN’04, pp. 320–329.CrossRefGoogle Scholar
  2. 52.
    Malaiya, Y. K. Antirandom testing: Getting the most out of black-box testing. In Proceedings of 6th IEEE International Symposium on Software Reliability Engineering (1995), ISSRE’95, IEEE Computer Society, pp. 86–95.Google Scholar
  3. 56.
    Mayrhauser, A., von, Bai, A., Chen, T., Anderson, C., and Hajjar, A. Fast antirandom (FAR) test generation. In Proceedings of the 3 rd IEEE International Symposium on High-Assurance Systems Engineering (1998), HASE ’98, IEEE Computer Society, pp. 262–269.Google Scholar
  4. 59.
    Mrozek, I. Analysis of multibackground memory testing techniques. International Journal of Applied Mathematics and Computer Science 20, 1 (Mar. 2010), 191–205.MathSciNetCrossRefGoogle Scholar
  5. 61.
    Mrozek, I., and Yarmolik, V. Optimal backgrounds selection for multi run memory testing. In Proceedings of the 11 th IEEE Workshop on Design and Diagnostics of Electronic Circuits and Systems (Apr. 2008), DDECS’08, pp. 332–338.Google Scholar
  6. 91.
    Tubbs, J. D. A note on binary template matching. Pattern Recognition 22, 4 (1989), 359–366.CrossRefGoogle Scholar
  7. 103.
    Wu, S. H., Jandhyala, S., Malaiya, Y. K., and Jayasumana, A. P. Antirandom testing: a distance-based approach. VLSI Design 2008 (Jan. 2008), 1–2.MathSciNetCrossRefGoogle Scholar
  8. 104.
    Wu, S. H., Malaiya, Y. K., and Jayasumana, A. P. Antirandom vs. pseudorandom testing. In Proceedings of the IEEE International Conference on Computer Design: VLSI in Computers and Processors (1998), ICCD’98, p. 221.Google Scholar
  9. 110.
    Yarmolik, S. V., and Mrozek, I. Multi background memory testing. In Proceedings of the 14 th International Conference Mixed design of integrated circuits and systems (Ciechocinek, Poland, June 2007), MIXDES’07, IEEE Computer Society, pp. 511–516.Google Scholar
  10. 121.
    Yiunn, D., Bin A’ain, A., Khor, and Ghee, J. Scalable test pattern generation (STPG). In Proceedings of the IEEE Symposium on Industrial Electronics Applications (Oct. 2010), ISIEA’10, pp. 433–435.Google Scholar
  11. 123.
    Zhang, B., and Srihari, S. Binary vector dissimilarity measures for handwriting identyfication. In Proceedings of the SPIE, Document Recognition and retrieval X (Santa Clara, California, USA, Jan. 2003), pp. 155–166.Google Scholar

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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Ireneusz Mrozek
    • 1
  1. 1.Bialystok University of TechnologyBialystokPoland

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