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Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency

Author

Listed:
  • Vibha Verma

    (University of Delhi)

  • Sameer Anand

    (University of Delhi)

  • P. K. Kapur

    (Amity University)

  • Anu G. Aggarwal

    (University of Delhi)

Abstract

Reliability of software products can be affected by several factors faced during the testing phase such as the generation of additional faults during the fault removal process, inefficiency or inaccuracy of team in completely removing faults, probability by which faults are removed, and difference between the number of failures and faults removed. These conditions have been termed as error generation, fault removal efficiency (FRE), imperfect debugging parameter, and fault reduction factor (FRF) respectively. In this paper, we have proposed a unified software reliability growth model (SRGM) to assess the impact of these parameters on the reliability and release schedule software. The error generation, imperfect debugging, and FRE parameters have been assumed to be constant while FRF is time-dependent modeled by exponential, Weibull, and delayed s-shaped distribution functions. These models can be represented using a single unified SRGM that reduces the difficulty of model selection. The special cases have been validated on two real-life fault datasets of Tandem computers and radar systems. Performance measures, the goodness of fit, and boxplot analysis show that the model fits the dataset very well. Further, the model that gives the best fit has been used for release planning for determining release and warranty time that minimizes development cost. The paper also analyses the sensitivity of cost parameters, the impact of change in error generation, FRE, FRF, and the reliability constraint on optimal timings. The results are highly encouraging for software managers and engineers and add value to the existing literature.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01653-x
    DOI: 10.1007/s13198-022-01653-x
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    References listed on IDEAS

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    1. Qiuying Li & Hoang Pham, 2017. "A testing-coverage software reliability model considering fault removal efficiency and error generation," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-25, July.
    2. 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.
    3. Bai, Jun & Pham, Hoang, 2006. "Cost analysis on renewable full-service warranties for multi-component systems," European Journal of Operational Research, Elsevier, vol. 168(2), pages 492-508, January.
    4. 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.
    5. P.K. Kapur & Hoang Pham & A. Gupta & P.C. Jha, 2011. "Software Reliability Assessment with OR Applications," Springer Series in Reliability Engineering, Springer, number 978-0-85729-204-9, February.
    6. 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.
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    Cited by:

    1. Rajat Arora & Rubina Mittal & Anu Gupta Aggarwal & P. K. Kapur, 2023. "Investigating the impact of effort slippages in software development project," 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. 14(3), pages 878-893, June.
    2. Ritu Bibyan & Sameer Anand & Anu G. Aggarwal & Abhishek Tandon, 2023. "Multi-release testing coverage-based SRGM considering error generation and change-point incorporating the random effect," 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. 14(5), pages 1877-1887, October.
    3. Tahere Yaghoobi & Man-Fai Leung, 2023. "Modeling Software Reliability with Learning and Fatigue," Mathematics, MDPI, vol. 11(16), pages 1-20, August.
    4. Shivani Kushwaha & Ajay Kumar, 2024. "Optimizing software release decisions: a TFN-based uncertainty modeling approach," 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. 15(8), pages 3940-3953, August.
    5. Umashankar Samal & Ajay Kumar, 2024. "A software reliability model incorporating fault removal efficiency and it’s release policy," Computational Statistics, Springer, vol. 39(6), pages 3137-3155, September.

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