Intelligent decision support system for COTS based software development

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Commercial Off-The-Shelf (COTS) Based Software Development (CBSD) process relies on identifying, evaluating and selecting COTS products that satisfy system requirements, and satisfy stakeholders' preferences. The methodologies that focus on the second target are mostly based on the consensus approach in which the stakeholders have to first agree on the solution evaluation criteria and their relative importance. Then, the developer team has to evaluate the functionality of different COTS candidates against the solution evaluation criteria to select the most suitable COTS. However, there are several problems with such approaches: (1) in many cases it not possible to harmonize concerns of the stakeholders and agree on the solution evaluation criteria; (2) means for trying out different scenarios to deal with conflicting stakeholders' preferences may be missing; (3) situations where one (or more) stakeholder changes his/her preferences during the negotiation process is not usually dealt with; (4) coalition formation among stakeholders is ignored; (5) uncertainty and interdependencies inherent in the evaluation process are sometimes left unaddressed; (6) repositories for reuse of information from previous evaluation processes are either centralized or left out; and (7) cases where stakeholders have differing degree of significance are usually ignored. In this research we suggest a radically different approach in which (a) initial consensus is not required; (b) the above deficiencies are fully addressed; and (c) experience repositories are decentralized and require little or no maintenance. The use of multi-agent systems (MAS) and ontology-based knowledge management (OKM) are unique points in this project. Implementing the system using MAS offers flexibility, expandability and hiding complexity from users and allows for intelligent message passing and knowledge level negotiation. OKM allows for dynamic classification and distribution of knowledge, adapting to diversified contents, representations and personalized styles; incorporates efficient retrieval mechanisms; and requires virtually less or no centralized management and maintenance.