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Regression Testing Prioritization, Selection and Reduction using Hybrid Criteria

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 95 - Number 7
Year of Publication: 2014
Nitika Sharma
Neha Malhotra

Nitika Sharma and Neha Malhotra. Article: Regression Testing Prioritization, Selection and Reduction using Hybrid Criteria. International Journal of Computer Applications 95(7):38-46, June 2014. Full text available. BibTeX

	author = {Nitika Sharma and Neha Malhotra},
	title = {Article: Regression Testing Prioritization, Selection and Reduction using Hybrid Criteria},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {95},
	number = {7},
	pages = {38-46},
	month = {June},
	note = {Full text available}


Regression testing is a software testing technique. Testing and validating the part of code are the activity performed within different phases. Tasks of regression testing are: Test Case Prioritization, Test Suite Selection, Test case reduction which give the guarantee that no intended fault is produced while modifying the code. This paper hybrid all the criteria's in different prospective with existing techniques. Selecting and choosing minimum number of test cases according to the result is our major goal. It will give solution to certain unnecessary results found after testing that further seem to be diminished in execution time. In our work we are formulizing the swarm algorithm for hybrid criteria. Hybrid criteria use Rank, Merge and Choice for building the test cases from test suite for minimizing the redundancy. Branch technique is used if one of test cases fails or does not show any result then next option can be used. Swarm algorithms give additional functions for having effective result with less time and effort. Initial seed value for hybrid criteria's is taken randomly. This research will lead to give better efficiency in regression testing using hybrid criteria. Path Coverage deals with the test case selection as it gives all the details of test cases.


  • A. K. and M. G. 2012. Multi Objective Test Suite. Minimization Using Quantum Inspired Multi Objective Differential Evolution Algorith . IEEE, Volume 71.
  • Aftab Ali Hader, Shahzad Rafiq and Aamer Nadeem. 2012. Test Suite Optimizaion Using Fuzzy Logic. IEEE.
  • Bharti suri, and S. S. 1924-1932. Implementing Ant Colony Optimization for Test Case Selection and Prioritization. International Journal On Computer Science and Engineering.
  • Bing JIANG, Yangminn MU and Zhihua Zhang. 2010. Research of Optimization Algorithm for Regression Testing Suite. (O. C. Laboratory, & Computer School, Eds. ) IEEE, Volume 2, pp. 303-306.
  • Chengying Mao, X. Y. 2012. Generating Test Data for Structural Testing Based on Ant Colony Optimization. 12th International Conference on Quality Software pp. 98-101. Xi'an, Shaanxi: IEEE.
  • Daniel Di Nardo, N. A. 2013. Coverage-Based Test Case Prioritisation: An Industrial Case Study. IEEE, pp. 302-311. Luembourg: Sixth International Conference on Software Testing, Verification and Validation.
  • Elie Shaccoour, fadi Zaraket and Wes masri. 2013. Coverage Specification forTtest Case Intent Preservation in Regression Testing. IEEE, pp. 392-395.
  • Geniana Ioana Laiu, O. A. 2012. Automatic Test Data Generation for Software Path Testing using Evolutionary Algorithms. Third International Conference on Emerging Intelligent Data and Web Technologies, pp. 1-8. Bucharest.
  • Ghinwa Baradhi, Nashat Mansour. 1997. A comparative Study of Five Regression Testing Algorithms. IEEE, pp. 174-182.
  • Gurinder singh, Dinesh gupta. 2013. An Intergarted to Test suite Selection Using ACO and Genetic Algorithm. IJARCSSE(Issue 6), pp. 1770-1778.
  • Harrold, M. J. 2009. Reduce,Reuse,Recycle,Recover: Techniques for Improved Regression Testing. IEEE.
  • Hualing zhao, Xiaoxia wu and Hanfeng chen 2010. A New Algorithm in Detecting Changepoint in Linear Regression Model. (C. o. Statistics, Ed. ) IEEE, pp. 2261-2264.
  • Jin chen, Mengxiang lin, Kai yu and Bing shao 2012. When The GUI Regression Test Failed, What Should Be Blamed. (B. U. School of Software, Ed. ) IEEE fifth international conference on software testing,verification and validation, pp. 467-470.
  • K. Karnavel, J. 2013. Automated Software Testing for Application Maintenance by Using Bee Colony Optimization Algorithms (BCO). Information Communication and Embedded Systems pp. 327-330. Chennai: IEEE.
  • Kropp, M. Introduction to Software Construction. University of Applied Sciences Northwestern Switzerland.
  • Luciano S. de Souza, P. B. 2011. A Multi-Objective Particle Swarm Optimization for Test Case Selection Based on Functional Requirements Coverage and Execution Effort. 23rd IEEE International Conference on Tools with Artificial Intelligence, pp. 245-252. Boca Raton.
  • Lulia STEFAN , Liviu MICLEA 2012. The Usage of Contextual Information to Develop the Data Test Vector. Automated Department.
  • Mai Daftedar, Mohamed Shalan 2012. Automated Pseudo-Random Regression Testing for GUI-Centeric Embedded Software. IEEE, pp. 293-298.
  • Md. Junaid arafeen, Hyunsook 2011. Adaptive Regression Testing Strategies: An Empirical Study. IEEE, pp. 130-139.
  • Nirmal Kumar Gupta, M. K. 2013. Improving GA Based Automated Test Data Generation Technique for Object Oriented Software. 3rd IEEE International Advance Computing Conference, pp. 249-253. Ghaziabad.
  • Osman Gokalp, A. U. 2012. Improving Performance of ACO Algorithms Using Crossover Mechanism Based on Mean of Pheromone Tables. International Symposium on Innovations in Intelligent Systems and Applications, pp. 1-4. Trabzon.
  • Roykrong Sukkerd, Ivan Beschastnikh, Jochen wuttke, Sai Zhang and Yurily Brun 2013. Understanding the Regression Failures Through Test-Passing Code Change. IEEE .
  • Rui Ding, X. F. 2012. Automatic Generation of Software Test Data Based on Hybrid Particle Swarm Genetic Algorithm. IEEE pp. 670-673. Kuala Lumpur: Symposium on Electrical & Electronics Engineering.
  • Sreedevi Sampath, Renee bryce and Atif M. Memon 2013. A Uniform Representation of Hybriid Criteria for Regression Testing. IEEE, Volume 39, pp. 1326-1343.
  • Toshihiko koju, Shingo Tokada and Norihisa doi 2003. Regression Test Selection Based on Intermediate Code for Virtual Machines. International Conference on Software Maintenance pp. 1-10. Department of Information and Computer Science.
  • Wang Jun, Z. Y. 2011. Test Case Prioritization Technique Based on Genetic Algorithm. International Conference on Internet Computing and Information Services, pp. 173 - 175. Hong Kong.
  • Yi, M. 2012. The Research of Path-Oriented Test Data Generation Based on a Mixed Ant Colony System Algorithm and Genetic Algorithm. 8th International Conference on Wireless Communications, Networking and Mobile Computing, pp. 1-4. Shanghai.