A generalized multi-upgradation SRGM considering uncertainty of random field operating environments

Gaurav Mishra (), P. K. Kapur () and Anu G. Aggarwal ()
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Gaurav Mishra: Amity University Uttar Pradesh
P. K. Kapur: Amity University Uttar Pradesh
Anu G. Aggarwal: University of Delhi

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 22, 328-336

Abstract: Abstract Nowadays software companies are releasing upgraded versions of applications or software on a weekly, fortnightly, and monthly basis. This is mainly to meet the customer's requirements and beat the market competition in terms of features, speed, reliability, security, and many more attributes like iOS, Android, Facebook, and others. Finally, this shows the importance of the multi-up-gradation of the software. During the last 4 decades, many SRGMs have been presented for single and multi-up-gradation of the applications to measure the number of bugs and reliability of applications. All these SRGMs were presented in the fixed settings of the software development environment, which is very much predictable. But after the release of the software, the field operating environment is very much unpredictable and random. That is the reason we call it a random field operating environment (RFOE). Numerous SRGMs have been presented with the assumption that operating environments and development settings are similar. We are unaware of the operating environments' uncertainties because these two environments are much different in practice. In this paper, we presented two multi-upgradation SRGMs to capture the uncertainty of bug detection rate per unit of time in the RFOE. We have examined the attainment of the given models using an actual failure data set. The results reveal that the goodness of fit and prognostication performance has improved significantly.

Keywords: Multi-upgradation; Software reliability growth models (SRGMs); Uncertainty; Non-homogeneous Poisson process (NHPP); Random field operating environment (RFOE) (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-023-01859-7

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