“BA-TPFâ€: A Novel Approach Towards Regression Test Case Optimization

  • Authors

    • Sandeep Dalal
    • Sudhi r
    • Kamna Solanki
    https://doi.org/10.14419/ijet.v7i4.21567

  • Abstract

    One of the most critical and expensive segment of software development is software testing. It is practically not feasible to conduct exhaustive testing on any software system due to cost and time constraints. Moreover, amendments and modifications in a software for the purpose of fixing failures is inevitable. Therefore, one can never guarantee that a software has been thoroughly tested. Testing the whole software system exhaustively by running the entire set of test cases after every modification is near to impossible. Hence, the software system is tested by running the optimized test suite for minimizing the cost and effort without compromising the quality of the test suite in terms of uncovering faults and providing better coverage based on many parameters. This paper presents a novel technique “BA-TPF†for multi-objective test suite optimization for enhancing path coverage with minimized repetition ratio and minimized test suite size.

  • References

    1. [1] B. Beizer. "Software Testing Techniques". Van Nostrand Reinhold, New York, NY, 1990.

      [2] G. Myers. "The Art of Software Testing", NY,USA: John Wiley, 1979.

      [3] P. Mathur. "Foundations of software testing". China Machine Press, 2008.

      [4] Kaner, J. Bach, and B. Pettichord,. “Lessons Learned in Software Testingâ€. John Wiley & Sons, 2008. Paul C. Jorgensen.†Software Testing:A Craftsman’s Approachâ€, CRC Press, 4th Edition..

      [5] W Wong, J. Horgan, S. London and H. Agrawal. "A study of effective regression testing in practice". Proceedings of IEEE Eighth International Symposium on Software Reliability Engineering. pp. 264-274, 1997. https://doi.org/10.1109/ISSRE.1997.630875.

      [6] S. Yoo and M. Harman. "Regression Testing Minimisation, Selection and Prioritization : A survey". Journal of software testing , Verification and Reliability, Vol. 22, No. 2, pp. 67-120, 2012. https://doi.org/10.1002/stv.430.

      [7] Z. Li, M. Harman and R. M. Hierons. "Search algorithms for regression test case". IEEE Transactions on Software Engineering, San Francisco, CA, USA, pp. 225-237, 2007.

      [8] S. Elbaum, A. Malishevsky and G.Rothermel. "Test case prioritization: A family of empirical studies". IEEE Transactions on Software Engineering, Vol. 28, No. 2, pp 159-182, 2002 https://doi.org/10.1109/32.988497.

      [9] Ansari, A., Khan, A., Khan, A., & Mukadam, K. (2016). “Optimized Regression Test Using Test Case Prioritizationâ€. Procedia Computer Science, vol. 79, pp 152-160. https://doi.org/10.1016/j.procs.2016.03.020.

      [10] Suri, B. and Singhal, S. (2015). "Understanding the Effect of Time-Constraint Bounded Novel Technique for Regression Test Selection and Prioritization" .International Journal of System Assurance Engineering and Management, vol. 6, no. 1, pp. 71-77. https://doi.org/10.1007/s13198-014-0244-3.

      [11] K. Solanki, Y. Singh, S. Dalal.â€Test Case Prioritization: An approach based on modified ant colony optimizationâ€. Proceedings of IEEE International Conference on Computer, Communication and Control. 2015 Sept; Indore: India .Available at IEEE-xplore Digital Library and SCOPUS.

      [12] K. Solanki, Y. Singh, S. Dalal.â€Experimental Analysis of m-ACO Technique for Regression Testingâ€. Indian Journal of Science and Technology, vol. 9, no. 30, https://doi.org/10.17485/ijst/2016/v9i30/86588.

      [13] Mao, C., and Chen, J. (2012). "Generating Test Data for Structural Testing based on Ant Colony Optimization." IEEE International Conference on Quality Software (QSIC), pp. 98-101.

      [14] Sharma, B., Girdhar, I., Taneja, M., Basia, P., Vadla, S., & Srivastava, P. R. (2011). â€Software coverage: a testing approach through ant colony optimizationâ€. International Conference on Swarm, Evolutionary, and Memetic Computing, pp. 618-625. https://doi.org/10.1007/978-3-642-27172-4_73.

      [15] Suri, B., and Singhal, S. (2011). "Implementing Ant Colony Optimization for Test Case Selection And Prioritization". International Journal on Computer Science and Engineering, vol. 3, no. 5, pp. 1924-1932.

      [16] Srivastava, P., R., and Baby K. (2010). "Automated Software Testing Using Meta-Heuristic Technique Based On An Ant Colony Optimization". International Symposium on Electronic System Design (ISED), pp. 235-240. https://doi.org/10.1109/ISED.2010.52.

      [17] Srivastava, P. R., Baby, K. M. and Raghurama, G. (2009). “An approach of optimal path generation using ant colony optimizationâ€. IEEE Conference TENCON 2009, pp. 1-6.

      [18] Singh, Y., Kaur, A. (2010). "Test Case Prioritization using Ant Colony Optimization". ACM Software Engineering Notes, vol. 35, no. 4, pp. 1-7. https://doi.org/10.1145/1811226.1811238.

      [19] Li, K., Zhang, Z., & Liu, W. (2009). “Automatic test data generation based on ant colony optimization†Fifth International Conference on Natural Computation.

      [20] Chen, X., Gu, Q., Zhang, X., & Chen, D. (2009). “Building prioritized pairwise interaction test suites with ant colony optimizationâ€. Ninth International Conference on Quality Software, pp. 347-352.

      [21] Li, H., and Lam, C., P. (2005). "An Ant Colony Optimization Approach to Test Sequence Generation for State Based Software Testing". IEEE International Conference on Quality Software, pp. 255-262.

      [22] Berndt, D., and Watkins, A. (2005). "High Volume Software Testing using Genetic Algorithm". 38th IEEE International Conference on System Sciences, pp. 318-330.

      [23] Rajappa, V., Biradar, A., and Panda, S. (2008). "Efficient Software Test Case Generation Using Genetic Algorithm Based Graph Theory". IEEE International Conference on Emerging Trends in Engineering and Technology, pp. 298-303.

      [24] Krishnamoorthi, R., and Mary, A. (2009). "Regression Test Suite Prioritization using Genetic Algorithms". International Journal of Hybrid Information Technology, vol.2, no. 3, pp. 35-52.

      [25] Srivastava, P., R., and Kim, T., H. (2009). "Application of Genetic Algorithms in Software Testing". International Journal of Software Engineering and it's Application, Science & Engineering Research Support Society, Republic of Korea, ISSN: 1738-9984, vol. 3, no. 4, pp. 87-96.

      [26] McCaffrey, J., D. (2009). "Generation of Pair-wise Test Sets using Genetic Algorithm". 33rd IEEE International Computer Software and Applications Conference, pp. 626-631.

      [27] Jayamala and V. Mohan. "Quality Improvement and Optimization of Test cases- A hybrid genetic algorithm based approach". ACM SIGSOFT Software Engg. Notes, Vol. 35, No. 3, pp. 1-14, 2010 https://doi.org/10.1145/1764810.1764824.

      [28] Kaur, A., and Goyal, S. (2011). "A Genetic Algorithm for Regression Test Case Prioritization using Code Coverage". International Journal on Computer Science and Engineering, vol. 3, no. 5, pp. 1839-1847.

      [29] Kaur, A., and Goyal, S. (2011). "A Genetic Algorithm for Fault Based Regression Test Case Prioritization". International Journal of Computer Applications, vol. 32, no. 8, pp. 975-987.

      [30] Rathore, A., Bohara, A., Prashil, R. G., Prashanth, T. S., & Srivastava, P. R. (2011). “Application of genetic algorithm and tabu search in software testingâ€. Proceedings of the Fourth Annual ACM Bangalore Conference, pp 23. https://doi.org/10.1145/1980422.1980445.

      [31] Singhal, S., Gupta, S., Suri, B., & Panda, S. (2016). “Multi-deterministic Prioritization of Regression Test Suite Compared: ACO and BCOâ€. Advanced Computing and Communication Technologies, pp. 187-194.

      [32] Dalal, S., and Chillar, R. (2013). "A Novel Technique for Generation of Test Cases Based on Bee Colony Optimization and Modified Genetic Algorithm". International Journal of Computer Applications, vol. 68, no. 19, pp. 12-17. https://doi.org/10.5120/11687-7359.

      [33] Kaur, A., and Goyal, S. (2011). "A Bee Colony Optimization Algorithm for Code Coverage based Test Suite Prioritization". International Journal of Engineering Science and Technology, vol. 3, no. 4 pp. 2786-2795.

      [34] Kulkarni, N., Singh, P., and Srivastava, P., R. (2011). "Test Case Optimization using Artificial Bee Colony Algorithm". Advances in Computing and Communications, Springer Berlin Heidelberg, pp. 570-579.

      [35] Dahiya, S., S., and Chhabra, J., K. (2010) "Application of Artificial Bee Colony Algorithm to Software Testing". Australian Software Engineering Conference, pp. 149-154.

      [36] Jeyamala, D., and Mohan, V. (2009). "ABC-Artificial Bee Colony Optimization based Test Suite Optimization Technique". International Journal of Software Engineering, vol. 2, no. 2, pp. 1-33.

      [37] Öztürk, M. M. (2017). “A bat-inspired algorithm for prioritizing test casesâ€. Vietnam Journal of Computer Science, 1-13.

      [38] Srivastava, P. R. (2017). “Path Generation for Software Testing: A Hybrid Approach Using Cuckoo Search and Bat Algorithmâ€. In Nature-Inspired Computing and Optimization , 409-424. Springer International Publishing. https://doi.org/10.1007/978-3-319-50920-4_16.

      [39] Srivastava, P. R., Bidwai, A., Khan, A., Rathore, K., Sharma, R., & Yang, X. S. (2014). An empirical study of test effort estimation based on bat algorithm. International Journal of Bio-Inspired Computation, 6(1), 57-70. https://doi.org/10.1504/IJBIC.2014.059966.

      [40] Srivastava, P. R., Pradyot, k., Sharma, D., Gouthami, K. P. (2015). Favourable test sequence generation in state base testing using bat algorithm. International Journal of Computer Applications in Technology, 51(4), 334-343. https://doi.org/10.1504/IJCAT.2015.070495.

      [41] Oluwagbemi, O. and H. Asmuni (2015), Automatic Generation of Test Cases from Activity Diagrams for UML Based Testing. Jurnal Teknologi,77(13).

      [42] Yang, X.S. (2010) A New Metaheuristic Bat-Inspired Algorithm, Nature Inspired Cooperative Strategies for Optimization, Spain.

      [43] Satapathy, S. C., Raja, N. S. M., Rajinikanth, V., Ashour, A. S., & Dey, N. (2016). “Multi-level image thresholding using Otsu and chaotic bat algorithmâ€. Neural Computing and Applications, 1-2

      [44] Dalal, S., & Solanki, K. (2018). “Performance Analysis of BCO-m-GA Technique for Test Case Selectionâ€. Indian Journal of Science and Technology, 8(1), pp1-10. https://doi.org/10.17485/ijst/2018/v11i9/110048.

      [45] Dalal, S., Chhillar, R. (2013) “Empirical study of root cause analysis of software failureâ€. ACM SIGSOFT Software Engineering Notes. 38(4):1–7. https://doi.org/10.1145/2492248.2492263.

  • Downloads

  • How to Cite

    Dalal, S., r, S., & Solanki, K. (2018). “BA-TPF”: A Novel Approach Towards Regression Test Case Optimization. International Journal of Engineering & Technology, 7(4), 3217-3222. https://doi.org/10.14419/ijet.v7i4.21567

    Received date: 2018-11-25

    Accepted date: 2018-11-25