Software testing process ordinarily expends no less than half of the aggregate cost required in programming advancement. Programming advancement associations spend significant part of their financial plan and time in testing related tasks. Software testing is an indispensable component in the Software Development Life Cycle (SDLC) and can outfit brilliant outcomes; if directed appropriately and successfully in an improved way. Lamentably, Software testing is frequently less formal and thorough than it ought to. Regression testing means to reveal all the undesired reactions of code corrections on rest of the code. Regression testing ensures that settling of programming deficiencies does not present whatever other issues, which were absent prior. Regression testing is iterative process, where size and many-sided quality of experiments continues expanding. Along these lines, Optimization of experiments is profoundly sought to finish the regression testing inside settled time and cost limitations. Streamlining of experiments amid regression testing is an open research problem as there is no single procedure which can supersede every other system on all parameters. Along these lines, researchers ought to evolve new experiment minimization systems for regression testing to improve its feasibility in view of different parameters. This paper reports a work on building up a novel minimization procedure for regression testing utilizing firefly based optimization.

Regression Testing,Test case Minimization, Soft computing ,Object Oriented Testing, Software Maintenance

[1] M. Utting and B. Legeard, Practical model-based testing: a tools approach. 2010.
[2] P. R. Srivastava, M. Ray, J. Dermoudy, B. Kang, and T. Kim, “Test Case Minimization and Prioritization Using CMIMX Technique *,” vol.333031, pp. 25–26.
[3] Z. Li, M. Harman, and R. M. Hierons, “Search algorithms for regression test case prioritization,” IEEE Trans. Softw. Eng., vol. 33, no. 4, pp.225–237, 2007.
[4] S. Elbaum, A. G. Malishevsky, and G. Rothermel, “Test case prioritization: A family of empirical studies,” IEEE Trans. Softw. Eng.,2002.
[5] P. Parashar, A. Kalia, and R. Bhatia, “How Time-Fault Ratio helps in Test Case Prioritization for Regression Testing,” no. 1, 2016.
[6] R. Singh and M. Santosh, “Test Case Minimization Techniques : A Review 1,2,” Int. J. Eng. Res. Technol., vol. 2, no. 12, pp. 1048–1056, 2013.
[7] B. S. Ahmed, “Test case minimization approach using fault detection and combinatorial optimization techniques for configuration-aware structural testing,” Eng. Sci. Technol. an Int. J., 2016.
[8] S. Biswas, M. S. Kaiser, and S. A. Mamun, “Applying Ant Colony Optimization in software testing to generate prioritized optimal path and test data,” in 2nd International Conference on Electrical Engineering and Information and Communication Technology, iCEEiCT 2015, 2015.
[9] E. Engström, P. Runeson, and M. Skoglund, “A systematic review on regression test selection techniques,” Information and Software Technology. 2010.
[10]S. Sharma and A. Singh, “Model-based test case prioritization using ACO: A review,” in 2016 4th International Conference on Parallel, Distributed and Grid Computing, PDGC 2016, 2016.
[11]Vandana and A. Singh, “Multi-objective test case minimization using evolutionary algorithms: A review,” in Proceedings of the International Conference on Electronics, Communication and Aerospace Technology, ICECA 2017, 2017, vol. 2017–Janua.
[12]M. Rani, “Review of Regression Test Case Selection Techniques,” vol. 3, no. 5, pp. 1029–1034, 2014.
[13]S. Yoo and M. Harman, “Regression Testing Minimisation, Selection and Prioritisation : A Survey,” Test. Verif. Reliab, vol. 00, pp. 1–7, 2007.
[14]T. L. Graves, M. J. Harrold, J. Kim, A. Porters, and G. Rothermel, “An empirical study of regression test selection techniques,” in Proceedings of the 20th International Conference on Software Engineering, 1998, pp. 188–197.
[15]H. Srikanth, L. Williams, and J. Osborne, “System test case prioritization of new and regression test cases,” in 2005 International Symposium on Empirical Software Engineering, ISESE 2005, 2005, vol. 00, no. c, pp. 64–73.
[16]P. McMinn and M. Holcombe, “The state problem for evolutionary testing,” … Evol. Comput. 2003, 2003.
[17]C. Catal and D. Mishra, “Test case prioritization: A systematic mapping study,” Softw. Qual. J., vol. 21, no. 3, pp. 445–478, 2013.
[18]B. Korel, L. H. Tahat, and M. Harman, “Test prioritization using system models,” in IEEE International Conference on Software Maintenance, ICSM, 2005, vol. 2005, pp. 559–568.
[19]P. Gaur and R. S. Singhal, “A critical review on test case prioritization and optimization using soft computing techniques,” International Journal of Control Theory and Applications. 2016.
[20]R. Kruse, C. Borgelt, C. Braune, S. Mostaghim, and M. Steinbrecher, Computational Intelligence: A Methodological Introduction. 2016.
[21]A. Alert and L. Grunske, “Test data generation with a Kalman filter-based adaptive genetic algorithm,” J. Syst. Softw., 2015.
[22]H. Duan, Q. Luo, G. Ma, and Y. Shi, “Hybrid Particle Swarm Optimization and Genetic Algorithm for Multi-UAV Formation Reconfiguration,” Ieee Comput. Intell. Mag., 2013.