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An ecological space based hybrid swarm-evolutionary algorithm for software reliability model parameter estimation

Author

Listed:
  • Sangeeta

    (Delhi Technological University)

  • Kapil Sharma

    (Delhi Technological University)

  • Manju Bala

    (Delhi University)

Abstract

Reliability analysis of the software has attracted a lot of attention of the software developers and researchers due to rapid growing need of software in routine life. The software reliability prediction by mathematical models is entirely centered on the estimation of parameter values, and the parameter estimation of the models poses a non-differential, nonlinear, and multimodal problem. A new algorithm based on the concept of ecological space, method of differential evolution (DE) and intelligent behavior of artificial bee colony (ABC) for optimizing the parameter values has been proposed in this paper. The exploration capability in ABC algorithm has been improved by introducing the concept of ecological space. Ecological space is one of the important factors for evolution and reflects the expansion of individual bee in search space. DE technique provides the diversity of bee’s population and faster convergence. The proposed algorithm has been tested with four standard failure datasets. Proficiency of proposed algorithm is also compared with other meta-heuristic algorithms namely ABC, genetic algorithm and particle swarm optimization. Further validation of proposed algorithm is done through comparing its efficiency with hybrid partilce swarm optimization and gravitational search Algorithm. Simulation results verify that proposed hybrid algorithm is very much effective in field of software reliability estimation and would be a competitive one among meta-heuristic optimization algorithms.

Suggested Citation

  • Sangeeta & Kapil Sharma & Manju Bala, 2020. "An ecological space based hybrid swarm-evolutionary algorithm for software reliability model parameter estimation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 77-92, February.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:1:d:10.1007_s13198-019-00926-2
    DOI: 10.1007/s13198-019-00926-2
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    References listed on IDEAS

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    1. Triet Pham & Hoang Pham, 2019. "A generalized software reliability model with stochastic fault-detection rate," Annals of Operations Research, Springer, vol. 277(1), pages 83-93, June.
    2. Rana Majumdar & P.K. Kapur & Sunil K. Khatri & A.K. Shrivastava, 2019. "Effort-based software release and testing stop time decisions," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 13(3), pages 179-193.
    3. Mohd Nadhir Ab Wahab & Samia Nefti-Meziani & Adham Atyabi, 2015. "A Comprehensive Review of Swarm Optimization Algorithms," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-36, May.
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