A large number of software reliability growth models (SRGMs) have been proposed during the past 30 years to estimate software reliability measures such as the number of remaining faults, software failure rate, and software reliability. Selection of an optimal SRGM for use in a particular case has been an area of interest for researchers in the field of software reliability. Tools and techniques for software reliability model selection found in the literature cannot be used with high confidence as they use a limited number of model selection criteria. For the first time, we developed a deterministic quantitative model based on a distance based approach (DBA) method, then applied it for evaluation, optimal selection, and ranking of SRGMs. DBA recognizes the need for relative importance of criteria for a given application, without which inter-criterion comparison could not be accomplished. It requires a set of model selection criteria, along with a set of SRGMs, and their level of criteria for optimal selection; and it successfully presents the results in terms of a merit value which is used to rank the SRGMs. We use two distinct, real data sets for demonstration of the DBA method. The result of this study will be a ranking of SRGMs based on the Euclidean composite distance of each alternative to the designated optimal SRGM.

Contribution: The main contribution is to provide practitioners and researchers with an insight in efficiently and effectively employing multi-attribute decision making (MADM) methods in e-learning website selection problems. Background: Advances in information systems and the Internet have resulted in e-learning websites becoming an important interface for learners. The selection of a particular website directly affects the end users' performance, with the objectives and expected outcomes of e-learning being largely dependent on the quality of the teaching processes and the effectiveness of online access. Evaluation and selection of these websites has thus become a decisive issue for learners and developers. Intended Outcomes: This paper is expected to provide decision support to leaders in education and educational organizations in effectively analyzing and managing their e-learning system. A knowledge-based system may be developed to develop and assess e-learning websites in a meaningful way. Application Design: A hybrid MADM method, fuzzy complex proportional assessment (COPRAS) is used to evaluate, rank, and select e-learning websites of ``C'' programming language. The fuzzy COPRAS method is validated by comparison with the technique for order preference by similarity to ideal solution, on an existing selection problem of 12 websites available in the open literature. Findings: Fuzzy COPRAS provides a comprehensive ranking of e-learning websites based on fitness degree values. The case study results rated tutorialspoint.com as the best of the e-learning websites considered, and howstuffworks.com was rated lowest. This paper shows that fuzzy COPRAS could be useful for e-learning practitioners, developers, and the researchers.

The current research work scrutinizes aluminium alloy 6101-graphite composites for their mechanical and tribological behaviour in dry sliding environments. The orthodox liquid casting technique had been used for the manufacturing of composite materials and imperilled to T6 heat treatment. The content of reinforcement particles was taken as 0, 4, 8, 12 and 16 wt.% of graphite to ascertain it is prospective as self-lubricating reinforcement in sliding wear environments. Hardness, tensile strength and flexural strength of cast Al6101 metal matrix and manufactured composites were evaluated. Hardness, tensile strength and flexural strength decreases with increasing volume fraction of graphite reinforcement as compared to cast Al6101 metal matrix. Wear tests were performed on pin on disc apparatus to assess the tribological behaviour of composites and to determine the optimum volume fraction of graphite for its minimum wear rate. Wear rate reduces with increase in graphite volume fraction and minimum wear rate was attained at 4 wt.% graphite. The wear was found to decrease with increase in sliding distance. The average co-efficient of friction also reduces with graphite addition and its minimum value was found to be at 4 wt.% graphite. The worn surfaces of wear specimens were studied through scanning electron microscopy. The occurrence of 4 wt.% of graphite reinforcement in the composites can reveal loftier wear possessions as compared to cast Al6101 metal matrix