Enhanced Classification Tree Method for Modeling Pairwise Testing

Easter Viviana Sandin, Radziah Mohamad


Software testing is one of the most important activities to produce a high-quality system, which can increase the trust level of users. There are many types of software testing. One of those testing is called exhaustive testing. Exhaustive testing is used to produce a test suite that will be used in other testing types such as unit testing, system testing, integration testing and also acceptance testing. However, exhaustive testing is infeasible and will be time consuming. Therefore, the combinatorial testing is proposed to solve the exhaustive testing problem. There are many techniques of combinatorial testing. The popular one is called pairwise testing. It also is known as Allpairs or 2-way testing. It involves the interaction of 2 parameters. In order to perform the pairwise testing, there are procedures that need to be fulfilled. The first procedure is modeling of System Under Test (SUT). There are many models that can be used to design the test suite for pairwise testing. In this paper, the comparison for modeling of SUT in pairwise testing is performed, and the enhancement of Classification Tree Method is proposed. An example based on steps of proposed model method is also provided.


Classification Tree Method; Modeling of SUT; Pairwise Testing;

Full Text:



S. K. Khalsa, and Y. Labicle, “An orchestrated survey of available algorithms and tools for combinatorial testing,” in 25th IEEE International Symposium on Software Reliability Engineering, ISSRE 2014, Naples, Italy, November 3-6, 2014, pp. 323–334.

P. Satish, and K. Rangarajan, “A preliminary survey of combinatorial test design modeling methods,” International Journal of Scientific & Engineering Research, vol. 7, no. 7, pp. 1455-1459, Jul. 2016.

P. Purohit, and Y. Khan, “An automated sequence model testing (ASMT) for improved test case generation using cloud integration,” International Journal of Computer Science and Information Technologies, vol. 6, no. 1, 488-494, 2015.

M. Brcic and D. Kalpic, “Combinatorial testing in software projects,” in MIPRO, 2012 Proceedings of the 35th International Convention, pp. 1508–1513, 2012.

L. P. Mudarakola and M. Padmaja, “The survey on artificial life techniques for generating the test cases for combinatorial testing,” International Journal of Research Studies in Computer Science and Engineering (IJRSCSE). vol. 2, no. 6, pp. 19-26, June 2015.

M. N. Borazjany, L. S. Ghandehari, Y. Lei, R. Kacker, and R. Kuhn, “An input space modeling methodology for combinatorial testing,” in 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2013, pp.372-381.

T. Kitamura, A. Yamada, G. Hatayama, C. Artho, E. H. Choi, N. T. B. Do, Y. Oiwa, and S. Sakuragi, “Combinatorial testing for treestructured test models with constraints,” in 2015 IEEE International Conference on Software Quality, Reliability and Security, pp. 141-150, 2015.

C. Nie, and H. Leung, “A survey of combinatorial testing,” ACM Computing Surveys, vol. 43, no. 2, Jan. 2011.

M. Patil, and P. J. Nikumbh, “Pair-wise testing using simulated annealing,” Procedia Technology, vol. 4, pp. 778-782, 2012.

D. R. Kuhn, R. N. Kacker, and Y. Lei, Introduction to Combinatorial Testing. London, UK: Chapman & Hall/CRC, London, 2013.

J. Bach and P. J. Schroeder, “Pairwise testing-a best practice that isn’t,” in Proceedings of the 22nd Pacific Northwest Software Quality Conference, 2004, pp.180–196.

L. Y. Xiang, A. R. A. Alsewari, and K. Z. Zamli, “Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT),” International Journal on Artificial Intelligence, vol. 2, Feb. 2015.

S. Udai, “A literature survey on combinatorial testing,” International Journal of Advanced Research in Computer Science and Software Engineering, vol. 4, no. 4, pp. 932-936, Apr. 2014.

G. Matthias, J. Wegener, and K. Grimm, “Test case design using classification trees and the classification-tree editor CTE,” in Proceedings of the 8th International Software Quality Week, vol. 95, 1995, pp. 30.

G. Mats and J. Offutt, “Input parameter modeling for combination strategies,” in Proceedings of the 25th Conference on IASTED International Multi-Conference (SE‟07), ACTA Press, 2007, pp.255- 260.

P. Satish, K. Sheeba, and K. Rangarajan, “Deriving combinatorial test design model from UML activity diagram,” in 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2013, pp. 331-337.

P. M. Kruse, Enhanced Test Case Generation with the Classification Tree Method. University of Berlin: Ph.D. Thesis, 2013.

T. J. Ostrand, and M. J. Balcer, “The category-partition method for specifying and generating functional tests,” Communications of the ACM, vol. 32, no. 6, pp. 676-686, 1988.

T. Y. Chen, P. L. Poonb, S. F. Tang and T. H. Tse, “On the identification of categories and choices for specification-based test case generation,” Information and Software Technology, vol. 46, no.13, pp. 887–898, 2004.

P. M. Kruse and J. Wegener, “Test sequence generation from classification trees,” in 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation, 2012, pp. 539-548.

T. B. Do, T. Kitamura, N. V. Tang, G. Hatayama, S. Sakuragi and H. Ohsaki, “Constructing test cases for N-wise testing from tree-based test models” in Proceedings of the Fourth Symposium on Information and Communication Technology, 2013, pp. 275–284.

P. Satish, A. Paul and K. Rangarajan, “Extracting the combinatorial test parameters and values from UML sequence diagrams,” in IEEE International Conference on Software Testing, Verification, and Validation Workshops, 2014, pp. 88-97.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN: 2180-1843

eISSN: 2289-8131