Weighted Criteria Hybrid Model for Ranking Commercial Off-The-Shelf Products

H. Ibrahim, B.H. Far (Canada), and A. Eberlein (UAE)

Keywords

COTSBased Development, Uncertainty Management,Bayesian Belief Networks, Analytic Hierarchy Process.

Abstract

The process of developing software applications by integrating one or more Commercial Off-The-Shelf (COTS) products has received much attention lately because it provides potential benefits such as shortening the development time, reducing effort and budget as well as improving the quality of the final product. However, COTS-based development (CBD), in particular the evaluation and selection of COTS components, is not a trivial task and associated with several challenges, including uncertainty inherent to COTS-related information and their vendors. Ignoring the uncertainty challenge negatively influences the quality of COTS selection decisions. In this paper, a hybrid model, composed of Bayesian network and analytic hierarchy process (AHP), is proposed to rank various COTS candidates and select the most fit one while explicitly considering uncertainty. The uncertainty in terms of incomplete and inaccurate information about COTS candidates is addressed using the Bayesian network model. On the other hand, AHP addresses inconsistency possibly existing in COTS candidates’ information. Furthermore, the Bayesian model is enhanced to allow the allocation of weights to evaluation criteria. A digital library system is selected as an example to investigate the impact of using weights on the belief about the satisfaction level for COTS candidates and illustrate how the hybrid model helps decision makers to select the most fit COTS candidate.

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