Testing coverage based NHPP software reliability growth modeling with testing effort and change-point

Anu Aggarwal (), Sudeep Kumar () and Ritu Gupta ()
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Anu Aggarwal: University of Delhi
Sudeep Kumar: Amity University Uttar Pradesh
Ritu Gupta: Manipal Academy of Higher Education

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 11, No 6, 5157-5166

Abstract: Abstract This paper investigates a software reliability growth model based on non-homogeneous Poisson process that includes coverage testing and change-points. The model integrate effort spent into a model to evaluate software reliability based on testing coverage. The amount of testing effort spent follows the Weibull distribution, while the amount of coverage is modeled by logistic, delayed S-shaped and exponential functions. Additionally, we look into the cost requirement-based software release time for exponential functions with a reliability constraint. We introduce the genetic algorithm, which is a powerful tool for dealing with search and optimization issues. For the purpose of testing the model's goodness of fit, two real failure datasets are used, and the model’s performance is analyzed based on goodness-of-fit metrics. By comparing the proposed model to perfect debugging models that have been described in the literature, it is demonstrated that the proposed model demonstrates notable advancements in this regard. The results of our analysis indicate that a software reliability estimation model should include change-points in a testing process if they exist.

Keywords: NHPP; Testing coverage; Software reliability growth model; Testing effort function (TEF); Change point (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-024-02504-7

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