Ant Colony Optimization Based Test Case Selection for Component Based Software

  • Authors

    • Palak Palak Research scholar, MDU, Rohtak
    • Preeti Gulia Assistant Professor, MDU, Rohtak
    2018-09-26
    https://doi.org/10.14419/ijet.v7i4.17565
  • Ant Colony Optimization, Components, Software Testing, Test case selection.

  • Reusability is one of the prime aspects of high quality software. Based on the concept of reusing the previous effort, Component based software engineering is a widely evolving software development paradigm that sets new challenges for testing team. The third party components need to be selected and assembled in development framework. Components interact with each other for various services and the interface between them can prove as the point of failure. As exhaustive testing of all interaction sequences is not possible, there is need for automated test case reduction and prioritization techniques to increase the efficiency of testing process. Ant Colony Optimization (ACO), a nature inspired optimization technique has wide range of applications in the field of software engineering. This paper presents an ACO based technique for test case selection for interaction testing of reusable software components.

     

     

  • References

    1. [1] T. Vale, I. Crnkovic, E. Santana, D. Almeida, P. Anselmo, S. Neto, Y. Cerqueira, S. Romero, and D. L. Meira, “Twenty-eight years of component-based software engineering,†J. Syst. Softw., vol. 111, pp. 128–148, 2016. https://doi.org/10.1016/j.jss.2015.09.019.

      [2] N. Sethi, S. Rani, and P. Singh, “Ants Optimization for Minimal Test Case Selection and Prioritization as to Reduce the Cost of Regression Testing,†Int. J. Comput. Appl., vol. 100, no. 17, pp. 48–54, 2014.

      [3] S. Yang, T. Man, and J. Xu, “Improved ant algorithms for software testing cases generation,†Sci. World J., vol. 2014, 2014.

      [4] G. Y.-H. Chen and P.-Q. Wang, “Test Case Prioritization in a Specification-based Testing Environment,†J. Softw., vol. 9, no. 8, pp. 2056–2065, 2014.

      [5] R. Malhotra, “Comparison of Search based Techniques for Automated Test Data Generation,†Int. J. Comput. Appl., vol. 95, no. 23, pp. 4–8, 2014.

      [6] T. Noguchi, H. Washizaki, and Y. Fukazawa, “History-Based Test Case Prioritization for Black Box Testing Using Ant Colony Optimization,†2015 IEEE 8th, vol. 1, pp. 2–3, 2015.

      [7] M. Mann and O. P. Sangwan, “Generating optimization and prioritizing optimal paths using ant colony,†vol. 5, no. 1, pp. 1–15, 2015.

      [8] A. Ansari, A. Khan, A. Khan, and K. Mukadam, “Optimized Regression Test Using Test Case Prioritization,†Procedia Comput. Sci., vol. 79, pp. 152–160, 2016. https://doi.org/10.1016/j.procs.2016.03.020.

      [9] C. Lu, J. Zhong, and C. Author, “An Efficient Ant Colony System For Coverage Based Test Case Prioritization,†in GECCO ’18 Companion, 2018, pp. 91–92.

      [10] H. Sharifipour, M. Shakeri, and H. Haghighi, “Structural test data generation using a memetic ant colony optimization based on evolution strategies,†Swarm Evol. Comput., vol. 40, pp. 76–91, 2018. https://doi.org/10.1016/j.swevo.2017.12.009.

      [11] F. Khan, M. Tahir, M. Babar, F. Arif, and S. Khan, “Framework for Better Reusability in Component Based Software Engineering,†J. Appl. Environ. Biol. Sci., vol. 6, no. 4S, pp. 77–81, 2016.

  • Downloads

  • How to Cite

    Palak, P., & Gulia, P. (2018). Ant Colony Optimization Based Test Case Selection for Component Based Software. International Journal of Engineering & Technology, 7(4), 2743-2745. https://doi.org/10.14419/ijet.v7i4.17565