Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging
Neha Gandhi, Neha Gondwal, Abhishek Tandon
DOI: http://dx.doi.org/10.15439/2017KM48
Citation: Proceedings of the 2017 International Conference on Information Technology and Knowledge Management, Ajay Jaiswal, Vijender Kumar Solanki, Zhongyu (Joan) Lu, Nikhil Rajput (eds). ACSIS, Vol. 14, pages 53–58 (2017)
Abstract. Open Source Software (OSS) has obtained widespread popularity in last few decades due to the exceptional contribution of some well established ones like Apache, Android, MySQL, LibreOffice, Linux etc. not only in the field of information technology but also in other sectors such as research, business and education. These systems are characterized by a huge shift in development pattern they adopt in comparison to proprietary software. Reliability modeling for such systems therefore is a growing area of research now days. Number of users adopting and working on refinement of such systems post-release play an indispensible role in their reliability growth. In this paper, we have proposed a software reliability growth model (SRGM) based on Non-homogeneous Poisson process (NHPP) based on number of users, under the phenomenon of Imperfect Debugging. The renowned Bass Model from Marketing based on the Theory of Diffusion of Innovation is used to depict the user growth phenomenon. Various fault content functions are considered in proposed models to represent imperfect debugging conditions and their performance is evaluated on fault dataset of GNOME 2.0. Four goodness-of-fit criteria namely Coefficient of Determination, Mean Square Error, Predictive Ratio Risk, and Predictive Power are used to calculate the estimation accuracy of all the proposed models and it has been observed that prediction capabilities of models based on imperfect debugging phenomenon is better than model assuming perfect debugging situation.
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