Regression Testing Cost Reduction Suite

Abstract

The estimated cost of software maintenance exceeds 70 percent of total software costs [1], and large portion of this maintenance expenses is devoted to regression testing. Regression testing is an expensive and frequently executed maintenance activity used to revalidate the modified software. Any reduction in the cost of regression testing would help to reduce the software maintenance cost. Test suites once developed are reused and updated frequently as the software evolves. As a result, some test cases in the test suite may become redundant when the software is modified over time since the requirements covered by them are also covered by other test cases. Due to the resource and time constraints for re-executing large test suites, it is important to develop techniques to minimize available test suites by removing redundant test cases. In general, the test suite minimization problem is NP complete. This paper focuses on proposing an effective approach for reducing the cost of regression testing process. The proposed approach is applied on real-time case study. It was found that the reduction in cost of regression testing for each regression testing cycle is ranging highly improved in the case of programs containing high number of selected statements which in turn maximize the benefits of using it in regression testing of complex software systems. The reduction in the regression test suite size will reduce the effort and time required by the testing teams to execute the regression test suite. Since regression testing is done more frequently in software maintenance phase, the overall software maintenance cost can be reduced considerably by applying the proposed approach.

Authors and Affiliations

Mohamed El-Din, Ismail Abd Taha, Hesham El-Deeb

Keywords

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  • EP ID EP162999
  • DOI 10.14569/IJACSA.2014.050818
  • Views 86
  • Downloads 0

How To Cite

Mohamed El-Din, Ismail Abd Taha, Hesham El-Deeb (2014). Regression Testing Cost Reduction Suite. International Journal of Advanced Computer Science & Applications, 5(8), 117-122. https://europub.co.uk/articles/-A-162999