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Amalgamation of Automated Test Case Generation Techniques with Data Mining Techniques: A Survey

by Yogita Dubey, Divakar Singh, Anju Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 134 - Number 5
Year of Publication: 2016
Authors: Yogita Dubey, Divakar Singh, Anju Singh

Yogita Dubey, Divakar Singh, Anju Singh . Amalgamation of Automated Test Case Generation Techniques with Data Mining Techniques: A Survey. International Journal of Computer Applications. 134, 5 ( January 2016), 18-22. DOI=10.5120/ijca2016907950

@article{ 10.5120/ijca2016907950,
author = { Yogita Dubey, Divakar Singh, Anju Singh },
title = { Amalgamation of Automated Test Case Generation Techniques with Data Mining Techniques: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 134 },
number = { 5 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016907950 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:33:20.712496+05:30
%A Yogita Dubey
%A Divakar Singh
%A Anju Singh
%T Amalgamation of Automated Test Case Generation Techniques with Data Mining Techniques: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 134
%N 5
%P 18-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

A testing module in the life cycle of a software development plays a crucial role for its development and its successful deployment using the defined cases. For this previous practitioner incorporated data mining techniques to reduce the number of test cases. During the software development process appropriate selection of unit tests is vital when many unit tests exist. Poor test selection may lead to Faults. This is true when the application is large and many developers are involved with some tests in which the developer can be unfamiliar and non-obvious relationships between application code and test code may be extant By the application of association rule mining and the unit test selection process and with extant selection techniques by comparison, Researchers facilitates a quantitative analysis of the advantages of heuristic and its disadvantages for the development where process patterns are stable. In test case generation technique data mining knowledge engineering area plays a vital role where the algorithm are capable of analyzing based on the pattern description such that the effective and accurate test cases can be generated, in this paper author presents a method to reduction the number of test suites by using mining methods thereby facilitating the mining from test cases. Here we are discussing about the Automated Test case Generation Techniques with Data Mining Techniques.

  1. Ajitha Ranjan.”Automated Requirements-Based test case Generation”. Communications of ACM, 2006
  2. T. Y. Chen and M. F. Lau. A new heuristic for test suite reduction. Information and Software Technology, 40(5):347-354, 1998.
  3. David Alex Lamb, “Software Engineering, planning for change,” Prentice Hall, Englewood Cliffs, NJ 07632, pp. 109–112, 1988.
  4. M. J. Harrold, R. Gupta, and M. L. Soffa. A methodology for controlling the size of a test suit. ACM Trans. on Soft.Eng. And Meth, 2(3):270-285, 1993.
  5. A. K. Jain, M. N. Murty, and P. J. Flynn. A Data clustering: review. ACM Computing Surveys, 31(3):264–323, 1999.
  6. Lilly Ramesh, “Knowledge Mining of Test Case System,” International Journal on Computer Science and Engineering Vol.2 (1), 2009, 69-73.
  7. Mark Last and Menahem Friedman.”The Data Mining approach to automated software testing.”.Communications of ACM, 2003.
  8. Martina marre and Antonia Bertolino, “using spanning sets for coverage testing”. IEEE transactions on software Engineering, vol.29.
  9. Remco R. Bouckaert.’weka Manual 3-6-1”. Software manual,June 4,2009,pp-11-14.
  10. Zhenyu Chen and Baowen Xu.”A novel approach for test suite reduction based on requirement relation contraction”.Communications of ACM, 2006.
  11. Vasilache S., and Tanaka J., "Synthesis of State Machines from Multiple Interrelated Scenarios Using Dependency Diagrams," Journal of Systemics, Cybernetics and Informatics, Vol.3, No.3, 2006.
  12. Lilly Raamesh and G.V. Uma “Reliable Mining of Automatically Generated Test Cases From Software Requirement Specification (SRS)” IJCSI Vol. 7, Issue 1, No. 3, January 2010.
  13. Abdelaziz M Khamis, Moheb R Girgis, and Ahmed S Ghiduk. Automatic software test data generation for spanning sets coverage using genetic algorithms. Computing and Informatics, 26(4):383–401, 2012.
  14. [MR Keyvanpour, H Homayouni, and Hasein Shirazee. Automatic software test case generation. Journal of Software Engineering, 5(3):91–101, 2011.
  15. Roshni Rajkumari and BG Geetha. Automated test data generation and optimization scheme using genetic algorithm. In Proceedings of International Conference on Software and Computer Applications (ICSCA 2011), 2011.
  16. Dharmalingam Jeya Mala, Elizabeth Ruby, and Vasudev Mohan. A hybrid test optimization framework-coupling genetic algorithm with local search technique. Computing and Informatics, 29(1):133–164, 2012.
  17. R. Pandita, T. Xie, N. Tillmann, and J. de Halleux, “Guided test generation for coverage criteria,” in Software Maintenance (ICSM), 2010 IEEE International Conference on, pp. 1–10, IEEE, 2010.
  18. Fayaz Ahmad Khan, Dr. Anil Kumar Gupta, Dibya Jyoti Bora Department of Computer Science and Applications, Barkatullah University Bhopal, (M.P) “An Efficient Approach to Test Suite Minimization for 100% Decision Coverage Criteria using K-Means Clustering Approach” IJAPRR ISSN (2350-1294) Vol. II, Issue VII, 2015
  19. Parag Deoskar , Dr. Divakar Singh and Dr. Anju Singh,“An Efficient Support Based Ant Colony Optimization Technique for Lung Cancer Data ,” International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 9, September 2013.
  20. Mrs. Nidhi Sing ,Dr. Divakar Singh , “The Improved K-Means with Particle Swarm Optimization” Journal of Information Engineering and Applications ISSN 2224-5782 (print) ISSN 2225-0506 (online) Vol.3, No.11, 2013.
  21. Surendra Kumar Chadokar , Dr. Divakar Singh and Ashutosh Singh , “Optimizing Network Traffic by Generating the Association rules using hybrid apriori genetic algorithm, “ 10th IEEE International Conference on Wireless and optical Communication Netwaork 2013
  22. Nidhi Singh , Dr. Divakar Singh, “The Improved K-Means with particle Swarm Optimization , Journal of Information Engineering and Application.
Index Terms

Computer Science
Information Sciences


Software Engineering Software Testing data mining test cases data item test suite Weka item set classifier Cluster Automated and Redundancy.