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Modelling software reliability growth through generalized inflection S-shaped fault reduction factor and optimal release time

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  • Vishal Pradhan
  • Ajay Kumar
  • Joydip Dhar

Abstract

The fault reduction factor (FRF) is a significant parameter for controlling the software reliability growth. It is the ratio of net fault correction to the number of failures encountered. In literature, many factors affect the behaviour of FRF, namely fault dependency, debugging time-lag, human learning behaviour and imperfect debugging. Besides this, several distributions, for example, inflection S-shaped, Weibull and Exponentiated-Weibull, are used as FRF. However, these standard distributions are not flexible to describe the observed behaviour of FRFs. This paper proposes three different software reliability growth models (SRGMs), which incorporate a three-parameter generalized inflection S-shaped (GISS) distribution as FRF. To model realistic SRGMs, time lags between fault detection and fault correction processes are also incorporated. This study proposed two models for the single release, whereas the third model is designed for multi-release software. Moreover, the first model is in perfect debugging, while the rest of the two are in an imperfect debugging environment. The extensive experiments are conducted for the proposed models with six single release and one multi-release data-sets. The choice of GISS distribution as an FRF improves the software reliability evaluation in comparison with the existing systems in the literature. Finally, the development cost and optimal release time are calculated in a perfect debugging environment.

Suggested Citation

  • Vishal Pradhan & Ajay Kumar & Joydip Dhar, 2022. "Modelling software reliability growth through generalized inflection S-shaped fault reduction factor and optimal release time," Journal of Risk and Reliability, , vol. 236(1), pages 18-36, February.
  • Handle: RePEc:sae:risrel:v:236:y:2022:i:1:p:18-36
    DOI: 10.1177/1748006X211033713
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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. Madhu Jain & T. Manjula & T.R. Gulati, 2014. "Imperfect debugging study of SRGM with fault reduction factor and multiple change point," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 6(2), pages 155-175.
    4. Anu Gupta Aggarwal & Neha Gandhi & Vibha Verma & Abhishek Tandon, 2019. "Multi-release software reliability growth assessment: an approach incorporating fault reduction factor and imperfect debugging," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 15(4), pages 446-463.
    5. 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.
    6. Peng, R. & Li, Y.F. & Zhang, W.J. & Hu, Q.P., 2014. "Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 37-43.
    7. Jiajun Xu & Shuzhen Yao, 2016. "Software Reliability Growth Model with Partial Differential Equation for Various Debugging Processes," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-13, January.
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