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NHPP-based change-point modeling for software reliability assessment and its application to software development management

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  • Yuka Minamino
  • Shinji Inoue
  • Shigeru Yamada

Abstract

We often observe a phenomenon that the stochastic behavior of software failure-occurrence time-interval changes notably due to the change of the testing-environment during testing activities. Testing-time when such phenomenon is observed is called change-point. We discuss a framework for software reliability growth modeling with the change of the change-point for improving the accuracy of software reliability assessment based on software reliability growth models, and develop specific non-homogeneous Poisson process (NHPP) models based on our modeling framework based on typical NHPP models. Also, we investigate the usefulness of our proposed models by conducting goodness-of-fit comparisons with corresponding existing models by using actual data. Further, we discuss the optimal software release problems, which are interesting issues in software development management, based on our proposed models. Finally, we show numerical examples for software reliability assessment based on our models and the derived optimal policies by using actual data.

Suggested Citation

  • Yuka Minamino & Shinji Inoue & Shigeru Yamada, 2016. "NHPP-based change-point modeling for software reliability assessment and its application to software development management," Annals of Operations Research, Springer, vol. 244(1), pages 85-101, September.
    • Handle: RePEc:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-016-2148-x
    DOI: 10.1007/s10479-016-2148-x
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    References listed on IDEAS

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    1. Can Huang & Luc Soete, 2008. "Policy forum," Science and Public Policy, Oxford University Press, vol. 35(10), pages 771-781, December.
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    Cited by:

    1. Subhashis Chatterjee & Ankur Shukla, 2017. "An Ideal Software Release Policy for an Improved Software Reliability Growth Model Incorporating Imperfect Debugging with Fault Removal Efficiency and Change Point," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-21, June.
    2. Vikas Dhaka & Nidhi Nijhawan, 2024. "Effect of change in environment on reliability growth modeling integrating fault reduction factor and change point: a general approach," Annals of Operations Research, Springer, vol. 340(1), pages 181-215, September.
    3. Mengmeng Zhu, 2022. "A new framework of complex system reliability with imperfect maintenance policy," Annals of Operations Research, Springer, vol. 312(1), pages 553-579, May.
    4. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 0. "Software release and testing stop time decision with change point," 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. 0, pages 1-12.
    5. P. K. Kapur & Saurabh Panwar & Ompal Singh & Vivek Kumar, 2022. "Joint optimization of software time-to-market and testing duration using multi-attribute utility theory," Annals of Operations Research, Springer, vol. 312(1), pages 305-332, May.
    6. 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.
    7. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 2020. "Software release and testing stop time decision with change point," 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(2), pages 196-207, July.
    8. Subhashis Chatterjee & Ankur Shukla & Hoang Pham, 2019. "Modeling and analysis of software fault detectability and removability with time variant fault exposure ratio, fault removal efficiency, and change point," Journal of Risk and Reliability, , vol. 233(2), pages 246-256, April.

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