Methodology for regression testing with open source tool

  • Authors

    • K. Hema Shankari
    • R. Thirumalai Selvi
    2017-12-21
    https://doi.org/10.14419/ijet.v7i1.1.9212
  • Regression testing, genetic algorithm, selenium tool, APFD metric, ANN.

  • Abstract

    The paper describes our methodology for optimizing regression testing that forms a major part of software maintenance. It necessitates the use of an automated testing tool, and we have selected Selenium, an open source tool. For simple projects, a formula is proposed that has been derived through data mining with Selenium. A genetic algorithm is added to this methodology for industry based projects, where the test cases are so large that they have to be grouped as Test Suites; this algorithm reconfigures Test suites in each cycle of regression testing. Commonly used APFD metric ignores fault severity but is included in our formula; this severity is determined by professional testers. The use of ANN to amend severity without manual intervention enhances the genetic algorithm. Tables presented in the paper are from both simple and industry projects. Comparison is made with IBM’S RFT, a proprietary tool for automated testing.

  • References

    1. [1] HemaShankari K, ThirumalaiSelvi R & Balasubramanian NV, “Industry Based Regression Testing Using IIGRTCP Algorithm and RFT Toolâ€, Lecture Notes in Engineering and Computer Science: Proceedings of The International Multi Conference of Engineers and Computer Scientists, pp.473-478, (2016).

      [2] Rothermel, G, Untch, R, Chu, C & Harrold, M, “Test case prioritization: An empirical studyâ€, IEEE International conference, on Software Maintenance, pp.179-188, (1999).

      [3] Pravin A & Srinivasan S, “An Efficient Algorithm for Reducing the Test Cases which is Used for Performing Regression Testingâ€, 2nd International Conference on Computational Techniques and Artificial Intelligence, pp. 194-197, (2013).

      [4] Elbaum S, Malishevsky A & Rothermel G, “Prioritizing test casesfor regression testingâ€, Proc. ACM SIGSOFT International Symposium on Software Testing and Analysis, pp.102–112, (2000).

      [5] Wong W, Horgan J, London S & Agrawal H, “A study of effective regression testing in practiceâ€, Proc. of the EighthIntl. Symp. On Softw, pp.230-238, (1997).

      [6] Beena R & Sarala S, “Code Coverage Based Test Case Selection And Prioritizationâ€, International Journal of Software Engineering & Applications, Vol.4, No.6, (2013).

      [7] Kavitha R & Sureshkumar N, “Test Case Prioritization for Regression Testing based on Severity of Faultâ€, International Journal on Computer Science and Engineering (IJCSE), (2010).

      [8] Musa S, Sultan A, Md AGA & Baharom S, “A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithmâ€, Research Inventy: International Journal of Engineering and Science, Vol.4, No.7, pp.54-64, (2014).

      [9] Sujatha M.K & Varun, K, “Requirements based Test Case Prioritization using Genetic Algorithmâ€, International Journal of Computer Science and Technology, Vol.1, No.2, pp.189-191, (2010).

      [10] Farooq QUA, Iqbal MZZ, Malik ZI & Nadeem A, “An approach for selective state machine based regression testingâ€, Proceedings of the 3rd International Workshop on Advances in Model-based Testing, pp.44–52, (2007).

      [11] Rothermel G, Untch R, Chu C & Harrold MJ, “Test case prioritization: an empirical studyâ€, Testing European Journal of Scientific Research, Vol.55, No.2, pp.261-274, (2011).

      [12] Elbaum S, Malishevsky A & Rothermel G, “Incorporating varying test costs and fault severities into test case prioritizationâ€, IEEE Proceedings of the 23rd International Conference on Software Engineering, pp. 329-338, (2001).

  • Downloads

  • How to Cite

    Hema Shankari, K., & Thirumalai Selvi, R. (2017). Methodology for regression testing with open source tool. International Journal of Engineering & Technology, 7(1.1), 133-137. https://doi.org/10.14419/ijet.v7i1.1.9212

    Received date: 2018-01-19

    Accepted date: 2018-01-19

    Published date: 2017-12-21