Experimental Analysis of “BA-TPF†Technique for Regression Test Optimization

  • Authors

    • Sandeep Dalal
    • Sudhi r
    • Kamna Solanki
    https://doi.org/10.14419/ijet.v7i4.21553

  • Regression testing focuses on finding those newer faults that may get introduced in the software during the process of fixing the older faults. Therefore, it becomes mandatory to re-test the software system after modifications and amendments to detect these undesired faults. The most important observation in this regard is to understand the fact that it becomes impractical for the software testing team to run the entire set of test cases again during regression testing phase due to cost, time and resource constraints. The ultimate way to deal this complexity of regression testing is to run the optimized set of test cases that can serve the purpose of regression testing without compromising the quality of the test suite. A novel technique “BA-TPF†has been proposed recently in this regard for test suite optimization in regression testing. This paper describes the experimental evaluation of the proposed technique and performance of the proposed technique has been evaluated using TCP, PRT and APPC metrices.

  • References

    1. [1] Leung, H. K., & White, L. (1989, October). Insights into regression testing (software testing). In Software Maintenance, 1989. Proceedings. Conference on (pp. 60-69). IEEE.

      [2] Rothermel, G., Untch, R. H., Chu, C., & Harrold, M. J. (1999). Test case prioritization: An empirical study. In Software Maintenance, 1999. (ICSM'99) Proceedings. IEEE International Conference on (pp. 179-188). IEEE. https://doi.org/10.1109/ICSM.1999.792604.

      [3] Rothermel, G., Untch, R. H., Chu, C., & Harrold, M. J. (2001). Prioritizing test cases for regression testing. IEEE Transactions on software engineering, 27(10), 929-948. https://doi.org/10.1109/32.962562.

      [4] Yoo, S., & Harman, M. (2012). Regression testing minimization, selection and prioritization: a survey. Software Testing, Verification and Reliability, 22(2), 67-120. https://doi.org/10.1002/stv.430.

      [5] Solanki, K., & Singh, Y. (2014). Importance of Selecting Test Cases for Regression Testing. IOSR Journal of Computer Engineering (IOSRJCE) e-ISSN, 2278-0661. https://doi.org/10.9790/0661-16444351.

      [6] Elbaum, S., Kallakuri, P., Malishevsky, A., Rothermel, G., & Kanduri, S. (2003). Understanding the effects of changes on the costâ€effectiveness of regression testing techniques. Software testing, verification and reliability, 13(2), 65-83. https://doi.org/10.1002/stvr.263.

      [7] Elbaum, S., Malishevsky, A. G., & Rothermel, G. (2002). Test case prioritization: A family of empirical studies. IEEE transactions on software engineering, 28(2), 159-182. https://doi.org/10.1109/32.988497.

      [8] Raju, S., & Uma, G. V. (2012). Factors oriented test case prioritization technique in regression testing using genetic algorithm. European Journal of Scientific Research, 74(3), 389-402.

      [9] Solanki, K., Dalal, S., A Literature study of various regression testing approaches. In Computing for Sustainable Global Development (INDIACom), 2018 fifth International Conference on 2018 Mar 15. IEEE. (In Press).

      [10] Solanki, K., Singh, Y., & Dalal, S. (2016). A Comparative Evaluation of “m-ACO†Technique for Test Suite Prioritization. Indian Journal of science and technology, 9(30). https://doi.org/10.17485/ijst/2016/v9i30/86423.

      [11] Solanki, K., Singh, Y., & Dalal, S. (2016). Experimental analysis of m-ACO technique for regression testing. Indian Journal of Science and Technology, 9(30). https://doi.org/10.17485/ijst/2016/v9i30/86588.

      [12] Suri, B., & Singhal, S. (2011). Implementing ant colony optimization for test case selection and prioritization. International journal on computer science and engineering, 3(5), 1924-1932.

      [13] GAO D, Guo X, Zhao L. (2015). Test case prioritization for regression testing based on ant colony optimization. In Software Engineering and Service Science (ICSESS), 6th IEEE International Conference on (pp. 275-279). IEEE. https://doi.org/10.1109/ICSESS.2015.7339054.

      [14] Solanki, K., Singh, Y., Dalal, S., & Srivastava, P. R. (2016). Test case prioritization: An approach based on modified ant colony optimization. In Emerging Research in Computing, Information, Communication and Applications (pp. 213-223). Springer, Singapore.

      [15] Suri, B., & Singhal, S. (2011). Analyzing test case selection & prioritization using ACO. ACM SIGSOFT Software Engineering Notes, 36(6), 1-5. https://doi.org/10.1145/2047414.2047431.

      [16] Suri, B., & Singhal, S. (2012, September). Literature survey of ant colony optimization in software testing. In Software Engineering (CONSEG), 2012 CSI Sixth International Conference on (pp. 1-7). IEEE.

      [17] Kaur, A., & Goyal, S. (2011). A genetic algorithm for fault-based regression test case prioritization. International Journal of Computer Applications, 32(8), 975-8887.

      [18] Panichella, A., Oliveto, R., Di Penta, M., & De Lucia, A. (2015). Improving multi-objective test case selection by injecting diversity in genetic algorithms. IEEE Transactions on Software Engineering, 41(4), 358-383. https://doi.org/10.1109/TSE.2014.2364175.

      [19] Raju, S., & Uma, G. V. (2012). Factors oriented test case prioritization technique in regression testing using genetic algorithm. European Journal of Scientific Research, 74(3), 389-402.

      [20] Catal, C. (2012, September). On the application of genetic algorithms for test case prioritization: a systematic literature review. In Proceedings of the second international workshop on evidential assessment of software technologies (pp. 9-14). ACM.

      [21] Suri, B., Mangal, I., & Srivastava, V. (2011). Regression test suite reduction using a hybrid technique based on BCO and genetic algorithm. Special Issue of International Journal of Computer Science & Informatics (IJCSI), ISSN (PRINT), 2231-5292.

      [22] Baudry, B., Fleurey, F., Jézéquel, J. M., & Le Traon, Y. (2005). Automatic test case optimization: A bacteriologic algorithm. IEEE Software, 22(2), 76-82. https://doi.org/10.1109/MS.2005.30.

      [23] Dobuneh, M. R. N., Jawawi, D. N., Ghazali, M., & Malakooti, M. V. (2014, September). Development test case prioritization technique in regression testing based on hybrid criteria. In Software Engineering Conference (MySEC), 2014 8th Malaysian (pp. 301-305). IEEE.

      [24] Silva, D., Rabelo, R., Campanha, M., Neto, P. S., Oliveira, P. A., & Britto, R. (2016, July). A hybrid approach for test case prioritization and selection. In Evolutionary Computation (CEC), 2016 IEEE Congress on (pp. 4508-4515). IEEE.

      [25] Mayan, J. A., & Ravi, T. (2015). Structural software testing: hybrid algorithm for optimal test sequence selection during regression testing. International Journal of Engineering and Technology (IJET), 7(1).

      [26] Walcott, K. R., Soffa, M. L., Kapfhammer, G. M., & Roos, R. S. (2006, July). Time aware test suite prioritization. In Proceedings of the 2006 international symposium on Software testing and analysis (pp. 1-12). ACM.

      [27] Hla, K. H. S., Choi, Y., & Park, J. S. (2008, July). Applying particle swarm optimization to prioritizing test cases for embedded real time software retesting. In Computer and Information Technology Workshops, 2008. CIT Workshops 2008. IEEE 8th International Conference on (pp. 527-532). IEEE.

      [28] Arafeen, M. J., & Do, H. (2013, March). Test case prioritization using requirements-based clustering. In Software Testing, Verification and Validation (ICST), 2013 IEEE Sixth International Conference on (pp. 312-321). IEEE.

      [29] Krishnamoorthi, R., & Mary, S. S. A. (2009). Factor oriented requirement coverage-based system test case prioritization of new and regression test cases. Information and Software Technology, 51(4), 799-808. https://doi.org/10.1016/j.infsof.2008.08.007.

      [30] Kavitha, R., Kavitha, V. R., & Kumar, N. S. (2010, October). Requirement based test case prioritization. In Communication Control and Computing Technologies (ICCCCT), 2010 IEEE International Conference on (pp. 826-829). IEEE.

      [31] Salehie, M., Li, S., Tahvildari, L., Dara, R., Li, S., & Moore, M. (2011, March). Prioritizing requirements-based regression test cases: A goal-driven practice. In Software Maintenance and Reengineering (CSMR), 2011 15th European Conference on (pp. 329-332). IEEE.

      [32] Di Nardo, D., Alshahwan, N., Briand, L., & Labiche, Y. (2015). Coverageâ€based regression test case selection, minimization and prioritization: A case study on an industrial system. Software Testing, Verification and Reliability, 25(4), 371-396. https://doi.org/10.1002/stvr.1572.

      [33] Dalal, S. & Sudhir (2018).BA-TPF: A novel approach towards Test suite optimization. International Journal of Engineering and Technology.In Press.

      [34] 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.

      [35] 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.

      [36] 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.

  • Downloads

  • How to Cite

    Dalal, S., r, S., & Solanki, K. (2018). Experimental Analysis of “BA-TPF” Technique for Regression Test Optimization. International Journal of Engineering & Technology, 7(4), 3135-3141. https://doi.org/10.14419/ijet.v7i4.21553