An investigation into the provision of a decision support system to evaluate software performance under uncertainty
by Md. Mahashin Mia; Mohammad Shahadat Hossain; Rashed Mustafa; Atiqur Rahman
International Journal of Computational Systems Engineering (IJCSYSE), Vol. 6, No. 4, 2021

Abstract: Disturbing the performance of a software has the capability to stop the everyday life activities of a certain area. Therefore, an earlier prediction of software performance could play an important role in saving time used for daily life activities. The signs of efficiency along with coverage and reliability in the system could be considered as a way to predict software performance. These factors cannot be determined accurately because of the presence of different categories of uncertainties. Therefore, this article presents a belief rule-based expert system (BRBES) that has the capability to predict software performance under uncertainty. Historical data of various software performances of the world with specific reference to efficiency as well as coverage and reliability have been considered in validating the BRBES. The dependability of our proposed BRBES's output is measured in comparison with fuzzy logic-based expert system (FLBES) and artificial neural networks (ANN)-based system, whereas our BRBES's results are found more reliable than that of FLBES and ANN. Therefore, this BRBES can be considered to predict the incidence of software performance in an area by taking account of the data related to the efficiency, coverage, and reliability.

Online publication date: Thu, 13-Jan-2022

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