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Multi-phase algorithm design for accurate and efficient model fitting

Author

Listed:
  • Joshua Steakelum

    (University of Massachusetts Dartmouth)

  • Jacob Aubertine

    (University of Massachusetts Dartmouth)

  • Kenan Chen

    (University of Massachusetts Dartmouth)

  • Vidhyashree Nagaraju

    (University of Massachusetts Dartmouth)

  • Lance Fiondella

    (University of Massachusetts Dartmouth)

Abstract

Recent research applies soft computing techniques to fit software reliability growth models. However, runtime performance and the distribution of the distance from an optimal solution over multiple runs must be explicitly considered to justify the practical utility of these approaches, promote comparison, and support reproducible research. This paper presents a meta-optimization framework to design stable and efficient multi-phase algorithms for fitting software reliability growth models. The approach combines initial parameter estimation techniques from statistical algorithms, the global search properties of soft computing, and the rapid convergence of numerical methods. Designs that exhibit the best balance between runtime performance and accuracy are identified. The approach is illustrated through nonhomogeneous Poisson process and covariate software reliability growth models, including a cross-validation step on data sets not used to identify designs. The results indicate the nonhomogeneous Poisson process model considered is too simple to benefit from soft computing because it incurs additional runtime with no increase in accuracy attained. However, a multi-phase design for the covariate software reliability growth model consisting of the bat algorithm followed by a numerical method achieves better performance and converges consistently, compared to a numerical method only. The proposed approach supports higher-dimensional covariate software reliability growth model fitting suitable for implementation in a tool.

Suggested Citation

  • Joshua Steakelum & Jacob Aubertine & Kenan Chen & Vidhyashree Nagaraju & Lance Fiondella, 2022. "Multi-phase algorithm design for accurate and efficient model fitting," Annals of Operations Research, Springer, vol. 311(1), pages 357-379, April.
    • Handle: RePEc:spr:annopr:v:311:y:2022:i:1:d:10.1007_s10479-021-04028-w
    DOI: 10.1007/s10479-021-04028-w
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    References listed on IDEAS

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    1. Ankur Choudhary & Anurag Singh Baghel & Om Prakash Sangwan, 2017. "An efficient parameter estimation of software reliability growth models using gravitational search algorithm," 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. 8(1), pages 79-88, March.
    2. Ramakanta Mohanty & Vadlamani Ravi & Manas Ranjan Patra, 2010. "The application of intelligent and soft-computing techniques to software engineering problems: a review," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 2(3), pages 233-272.
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