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A multi-release software reliability modeling for open source software incorporating dependent fault detection process

Author

Listed:
  • Mengmeng Zhu

    (Rutgers University)

  • Hoang Pham

    (Rutgers University)

Abstract

The increasing dependence of our modern society on software systems has driven the development of software products become even more competitive and time-consuming. Single release software product no longer meets the increasing market requirements. Thereby it is important to release multiple version software products in order to add new features in the next release and fix remaining faults from previous release. In this paper, we develop a multi-release software reliability model with consideration of the remaining software faults from previous release and the new introduced-faults (from newly added features). Additionally, dependent fault detection process is taken into account in this research. In particular, the detection of a new fault for developing the next release depends on the detection of the remaining faults from previous release and the detection of the new introduced-faults. The proposed model is validated on the open source software project datasets with multiple releases.

Suggested Citation

  • Mengmeng Zhu & Hoang Pham, 2018. "A multi-release software reliability modeling for open source software incorporating dependent fault detection process," Annals of Operations Research, Springer, vol. 269(1), pages 773-790, October.
    • Handle: RePEc:spr:annopr:v:269:y:2018:i:1:d:10.1007_s10479-017-2556-6
    DOI: 10.1007/s10479-017-2556-6
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    References listed on IDEAS

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    1. Etgar, Ran & Gelbard, Roy & Cohen, Yuval, 2017. "Optimizing version release dates of research and development long-term processes," European Journal of Operational Research, Elsevier, vol. 259(2), pages 642-653.
    2. P. K. Kapur & H. Pham & A. Gupta & P. C. Jha, 2011. "Software Reliability Growth Models," Springer Series in Reliability Engineering, in: Software Reliability Assessment with OR Applications, chapter 0, pages 49-95, Springer.
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    Cited by:

    1. Subhashis Chatterjee & Deepjyoti Saha & Akhilesh Sharma & Yogesh Verma, 2022. "Reliability and optimal release time analysis for multi up-gradation software with imperfect debugging and varied testing coverage under the effect of random field environments," Annals of Operations Research, Springer, vol. 312(1), pages 65-85, May.
    2. Mengmeng Zhu & Hoang Pham, 2022. "A generalized multiple environmental factors software reliability model with stochastic fault detection process," Annals of Operations Research, Springer, vol. 311(1), pages 525-546, April.
    3. Jia Huang & Hu-Chen Liu & Chun-Yan Duan & Ming-Shun Song, 2022. "An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method," Annals of Operations Research, Springer, vol. 312(1), pages 235-258, May.
    4. 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.
    5. 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.
    6. Vibha Verma & Sameer Anand & P. K. Kapur & Anu G. Aggarwal, 2022. "Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency," 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. 13(5), pages 2429-2441, October.

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