A Hybrid Approach for Test Case Prioritization using PSO Based on Software Quality Metrics

  • Authors

    • K Senthil Kumar
    • A Muthukumaravel
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16046
  • Regression Testing, Test Case Prioritization, Test Case Optimization, Particle Swarm Optimization, Cuckoo Search, Software metrics, Quantitative measure.

  • Abstract

    Effective functionality checking of any software application is the crucial event that determines the quality of outcome obtained.  Generally, checking scenarios that involves multiple test cases in mixture with multiple components is time consuming and also increases the quality assurance cost. Selection of suitable method/approach for optimization and prioritization of test cases as well as appropriate evaluation of the application would result in reduction of fault detection effort without appreciable information loss and further would also significantly decrease the clearing up cost. In the proposed method, test cases are optimized and then prioritized by Particle Swarm Optimization algorithm (PSO) and Improved Cuckoo Search algorithm (ICSA), respectively. Finally, the result will be evaluated for software quality measures.

     

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  • How to Cite

    Senthil Kumar, K., & Muthukumaravel, A. (2018). A Hybrid Approach for Test Case Prioritization using PSO Based on Software Quality Metrics. International Journal of Engineering & Technology, 7(3.12), 300-303. https://doi.org/10.14419/ijet.v7i3.12.16046

    Received date: 2018-07-22

    Accepted date: 2018-07-22

    Published date: 2018-07-20