Call for Paper - August 2022 Edition
IJCA solicits original research papers for the August 2022 Edition. Last date of manuscript submission is July 20, 2022. Read More

Pairwise Test Case Generation for Less Number of Test- Case Sets

IJCA Proceedings on International Conference on Advances in Computer Applications 2012
© 2012 by IJCA Journal
ICACA - Number 1
Year of Publication: 2012
Shalini Gupta
Avdhesh Gupta

Shalini Gupta and Avdhesh Gupta. Article: Pairwise Test Case Generation for Less Number of Test- Case Sets. IJCA Proceedings on International Conference on Advances in Computer Applications 2012 ICACA(1):23-26, September 2012. Full text available. BibTeX

	author = {Shalini Gupta and Avdhesh Gupta},
	title = {Article: Pairwise Test Case Generation for Less Number of Test- Case Sets},
	journal = {IJCA Proceedings on International Conference on Advances in Computer Applications 2012},
	year = {2012},
	volume = {ICACA},
	number = {1},
	pages = {23-26},
	month = {September},
	note = {Full text available}


Software testing is the process of analyzing a software item to detect the differences between existing and required conditions (that is, bugs) and to evaluate the features of the software items. Software testing is an activity that should be done throughout the whole development process. Pairwise testing primarily targets faults caused by interactions between two parameters. However, some faults can be caused by interactions involving more than two parameters. Those faults cannot effectively be detected by pairwise testing. In this research work, we presented an algorithm to generate effective and less number of test cases using pairwise testing technique. The pairwise testing approach is basically based on the fact that the majority of possible errors/faults/bugs occur when two modules/parameters values interact. This proposed algorithm can be used efficiently in various realms of software products. In future we can plan to reduce the number of test cases by using the degree of coverage of three and four-wise in efficient way. Ultimately this will reduce the total number of test cases and provide only effective and efficient test case set and thus it will also save time for both software developers as well as for software testers.


  • Pedro Flores, YoonsikCheon, PWiseGen: Generating Test Cases for Pairwise Testing Using Genetic Algorithms, IEEE International Conference on Computer Science and Automation Engineering (CSAE 2011), Shanghai, China, June 10-12, 2011.
  • JacekCzerwonka, Pairwise Testing in Real World Practical Extensions to Test Case Generators, Microsoft Corporation, February 2008.
  • Gilles Perrouin, SagarSen, Jacques Klein, Benoit Baudry, Yves le TraonLassy, Automated and Scalable T-wise Test Case Generation Strategies for Software Product Lines, Proceeding ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation, Pages 459-468, EEE Computer Society Washington, DC, USA,2010.
  • James Bach, Patrick J. Schroeder, Pairwise Testing: A Best Practice That Isn't, 22nd Annual Pacific Northwest Software Quality Conference, 2004.
  • Kuo-Chung Tai, Yu Lei, A Test Generation Strategy for Pairwise Testing, IEEE Transaction on Software Engineering, Volume 8, No. 1, Washington, DC, 13 November 1998.
  • Kevin Burr, William Young, Combinatorial Test Techniques: Table-based Automation, Test Generation and Code Coverage, Software Engineering Analysis Lab, Nortel. 82
  • Jerry Huller, Reducing Time to Market with Combinatorial Design Method Testing, USA, December 2005.
  • G. Bernet, L. Bouaziz, and P. LeGall, A Theory of Probabilistic Functional Testing, Proceedings of the 1997 International Conference on Software Engineering, pp. 216 –226,1997.
  • B. Beizer, Software Testing Techniques, Second Edition, Van Nostrand Reinhold Company Limited, 1990.
  • S. Beydeda and V. Gruhn, An integrated testing technique for component-based software,? ACS/IEEE International Conference on Computer Systems and Applications, pp 328 – 334, June 2001.
  • A. Bertolino, P. Inverardi, H. Muccini, and A. Rosetti, An approach to integration testing based on architectural descriptions, Proceedings of the IEEE ICECCS- 97, pp. 77-84, 1997.
  • J. B. Good Enough and S. L. Gerhart, Toward a Theory of Test Data Selection, IEEE Transactions on Software Engineering, pp. 156-173, June 1997.
  • D. Gelperin and B. Hetzel, The Growth of Software Testing, Communications of the ACM, Volume 31 Issue 6, pp. 687-695, June 1988.
  • J. Hartmann, C. Imoberdorf, and M. Meisinger, UML-Based Integration Testing, Proceedings of the International Symposium on Software Testing and Analysis, ACM SIGSOFT Software Engineering Notes, August 2000.
  • W. E. Howden, Functional Testing and Design Abstractions, The Journal of System and Software, Volum 1, pp. 307-313, 1980. 83
  • P. Jalote and Y. R. Muralidhara, A coverage based model for software reliability estimation, Proceedings of First International Conference on Software Testing, Reliability and Quality Assurance, pp. 6 –10 (IEEE), 1994.
  • E. F. Miller, ?Introduction to Software Testing Technology, Tutorial: Software Testing & Validation Techniques, Second Edition, IEEE Catalog No. EHO 180-0, pp. 4-16.
  • D. Richardson, O'Malley and C. Tittle, Approaches to specification-based testing, ACM SIGSOFT Software Engineering Notes, Volume 14 , Issue 9, pp. 86 – 96 1989.
  • S. Redwine& W. Riddle, Software technology maturation, Proceedings of the Eighth International Conference on Software Engineering, pp. 189-200, May 1985.
  • M. Shaw, Prospects for an engineering discipline of software, IEEE Software, pp. 15-24, November 1990.
  • L. J. White and E. I. Cohen, A Domain Strategy for Computer Program Testing, IEEE Transactions on Software Engineering, pp. 247-257, May 1980.
  • J. A. Whittaker, What is Software Testing? And Why Is It So Hard? IEEE Software, pp. 70-79, January 2000.
  • R. Mandl. Orthogonal Latin Squares: An application of experiment design to compiler testing. Communications of the ACM, 28(10):1054-1058, October 1985. 84
  • Y. Lei and K. C. Tai. In-parameter-order: A test generation strategy for pair-wise testing. In Proceedings of the third IEEE High Assurance Systems Engineering Symposium, pages 254-261. IEEE, November 1998.
  • D. M. Cohen, S. R. Dalal, J. Parelius, and G. C. Patton. The Combinatorial Design Approach to Automatic Test Generation. IEEE Software, pages 83-88, September 1996.
  • A. W. Williams and R. L. Probert. A practical strategy for testing pair-wise coverage of network interfaces. In Proceedings of the 7th International Symposium on Software Reliability Engineering (ISSRE96), White Plains, New York, USA, Oct 30 - Nov 2, 1996, Nov 1996.
  • A. W. Williams. Determination of test configurations for pair-wise interaction coverage. In Proceedings of the 13th International Conference on the Testing of Communicating Systems (TestCom2000), Ottawa,Canada, August 2000, pages 59-74, August 2000.
  • Karen Meagher. Covering Arrays on Graphs: Qualitative independence Graphs and extremal Set partition Theory. Chapter 2.
  • Mats Grindal, Jeff Offutt, Sten F. Andler. Combination Testing Strategies: A Survey. GMU Technical Report ISE-TR-04-05, July 2004
  • N. P. Kropp, P. J. Koopman, and D. P. Siewiorek. Automated robustness testing of off-the-shelf software components. In Proceedings of FTCS'98: Fault Tolerant Computing Symposium, June 23-25, 1998 in Munich, Germany, pages 230-239. IEEE, 1998.
  • Macario Polo Usaola and Beatriz Pérez Lamancha, A framework and a web implementation for combinatorial testing.