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A Test Prioritization Algorithm That Cares for "Don't Care" Values and Higher Order Combinatorial Coverage

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Published:11 January 2018Publication History
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Abstract

The efficiency of prioritization algorithms depends on how early the faults are detected. In this paper, we present a novel prioritization algorithm for combinatorial testing. Our approach takes ACTS tool generated test cases with "don't care" values as the starting point and refines them for increased effectiveness without increasing the number of test cases. Our algorithm maximizes the number of higher order combinations tested, by filling the "don't care" values in the test suite effectively. It also orders the test cases using a cost function that includes higher order coverage, thereby achieving early fault detection. The effectiveness of our algorithms is demonstrated by performing a comparative evaluation using the metric t way Rate of Fault Detection, on 2 real life case studies and numerous synthetic covering arrays of different sizes. The results show that our algorithms perform better in terms of covering higher order pairs and also faster.

References

  1. Bryce RC, Colbourn CJ. Test prioritization for pairwise interaction coverage. In ACM SIGSOFT Software Engineering Notes 2005;30(4): 1-7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bryce RC, Sampath S, Memon AM. Developing a single model and test prioritization strategies for event-driven software. Software Engineering, IEEE Transactions 2011; 37(1):48-64. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bryce RC, Sampath S, Pedersen JB, Manchester S. Test suite prioritization by cost-based combinatorial interaction coverage. International Journal of System Assurance Engineering and Management 2011; 2(2):126-34.Google ScholarGoogle Scholar
  4. Bryce, Renée C., and Atif M. Memon. Test suite prioritization by interaction coverage. In Workshop on Domain specific approaches to software test automation in conjunction with the 6th ESEC/FSE joint meeting 2007; 1-7. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bryce, Renée C., and Charles J. Colbourn. Prioritized interaction testing for pair-wise coverage with seeding and constraints. Information and Software Technology 2006; 48(10): 960-970.Google ScholarGoogle Scholar
  6. Chen X, Gu Q, Zhang X, Chen D. Building prioritized pairwise interaction test suites with ant colony optimization. In Quality Software,QSIC'09. 9th International Conference on 2009; (pp. 347-352). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Choi EH, Kitamura T, Artho C, Yamada A, Oiwa Y. Priority Integration for Weighted Combinatorial Testing. In Computer Software and Applications Conference (COMPSAC), IEEE 39th Annual 2015 (Vol. 2, pp. 242-247). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Colbourn CJ. Combinatorial aspects of covering arrays. Le Matematiche (Catania) 2004; 58(121-167):0-10.Google ScholarGoogle Scholar
  9. Czerwonka J. Pairwise testing in the real world: Practical extensions to test-case scenarios. In Proceedings of 24th Pacific Northwest Software Quality Conference, Citeseer 2006; 419-430.Google ScholarGoogle Scholar
  10. Ferrer J, Kruse PM, Chicano F, Alba E. Evolutionary algorithm for prioritized pairwise test data generation. In Proceedings of the 14th annual conference on Genetic and evolutionary computation 2012; (pp. 1213-1220). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Gao SW, Lv JH, Du BL, Colbourn CJ, Ma SL. Balancing Frequencies and Fault Detection in the In-Parameter-Order Algorithm. Journal of Computer Science and Technology 2015; 30(5):957-68Google ScholarGoogle Scholar
  12. Huang R, Chen J, Zhang T, Wang R, Lu Y. Prioritizing variable-strength covering array. InComputer Software and Applications Conference (COMPSAC) IEEE 37th Annual 2013; (pp. 502-511). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Huang R, Xie X, Towey D, Chen TY, Lu Y, Chen J. Prioritization of combinatorial test cases by incremental interaction coverage. International Journal of Software Engineering and Knowledge Engineering 2013; 23(10):1427-57.Google ScholarGoogle Scholar
  14. Kuhn, D. Richard, Raghu N. Kacker, and Yu Lei. Introduction to combinatorial testing. CRC Press,2013 Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kuhn, D. Richard, Raghu N. Kacker, and Yu Lei. Introduction to combinatorial testing. CRC Press,2013 Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Lei Y, Kacker R, Kuhn DR, Okun V, Lawrence J. IPOG/IPOG?D: efficient test generation for multi?way combinatorial testing. Software Testing, Verification and Reliability 2008;18(3):125-48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. National Institute of Standards and Technology (NIST), Automated Combinatorial Testing for Software (ACTS), http://csrc.nist.gov/groups/SNS/acts/documents/comparison-report.html . {13 April 2016}.Google ScholarGoogle Scholar
  18. Nie C, Leung H. A survey of combinatorial testing. ACM Computing Surveys (CSUR). 2011;43(2):11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Petke J, Yoo S, Cohen MB, Harman M. Efficiency and early fault detection with lower and higher strength combinatorial interaction testing. In Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering 2013; (pp. 26-36). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Qu X, Cohen MB, Rothermel G. Configuration-aware regression testing: an empirical study of sampling and prioritization. In Proceedings of the 2008 international symposium on Software testing and analysis 2008; (pp. 75-86). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Qu X, Cohen MB, Woolf KM. Combinatorial interaction regression testing: A study of test case generation and prioritization. In Software Maintenance, 2007. ICSM 2007. IEEE International Conference on 2007;(pp. 255-264). IEEE.Google ScholarGoogle Scholar
  22. Qu X, Cohen MB. A study in prioritization for higher strength combinatorial testing. In Software Testing, Verification and Validation Workshops (ICSTW), IEEE Sixth International Conference on 2013 (pp. 285-294). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Rothermel G, Untch RH, Chu C, Harrold MJ. Prioritizing test cases for regression testing. Software Engineering, IEEE Transactions 2001; 27(10): 929-48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Sampath S, Bryce R, Memon AM. A uniform representation of hybrid criteria for regression testing. Software Engineering, IEEE Transactions 2013; 39(10):1326-44. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sampath S, Bryce RC, Jain S, Manchester S. A tool for combination-based prioritization and reduction of user-session-based test suites. InSoftware Maintenance (ICSM), 27th IEEE International Conference on 2011; (pp. 574-577). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Satisfice, Inc.,ALLPAIRS Test case generation tool (Version 1.2.1) http://www.satisfice.com/tools.shtml, {13 April 2016}.Google ScholarGoogle Scholar
  27. Software-artifact Infrastructure Repository, http://sir.unl.edu/portal/index.php {13 April 2016}.Google ScholarGoogle Scholar
  28. Srikanth H, Cohen MB, Qu X. Reducing field failures in system configurable software: Cost-based prioritization. In 20th International Symposium on Software Reliability Engineering 2009; (pp. 61-70). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Wu H, Nie C, Kuo FC. Test suite prioritization by switching cost. InSoftware Testing, Verification and Validation Workshops (ICSTW), 2014 IEEE Seventh International Conference on 2014; (pp. 133-142). IEEE Google ScholarGoogle ScholarDigital LibraryDigital Library

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