Intelligent Support for Selection of COTS Products

Intelligent Decision Support is considered in unstructured decision situations characterized by one or more of the following factors: complexity, uncertainty, multiple groups with a stake in the decision outcome (multiple stakeholders), a large amount of information (especially company data), and/or rapid change in information. Support here means to provide access to information that would otherwise be unavailable or difficult to obtain; to facilitate generation and evaluation of solution alternatives, and to prioritize alternatives by using explicit models that provide structure for particular decisions. Integration of commercial off the shelf (COTS) products as elements of larger systems is a promising new paradigm. In this paper, we focus on the selection of COTS products. This is characterized as a problem with a high degree of inherent uncertainty, incompleteness of information, dynamic changes and involvement of conflicting stakeholder interests. A semi-formal problem description is given. We derive requirements on Decision Support Systems for COTS selection and discuss ten existing approaches from the perspective of those requirements. As a result, we propose an integrated framework called COTS-DSS combining techniques and tools from knowledge management and artificial intelligence, simulation and decision analysis.

[1]  Barry W. Boehm,et al.  COTS-Based Systems Top 10 List , 2001, Computer.

[2]  Sallie Gregor,et al.  Storyboard Process to Assist in Requirements Verification and Adaptation to Capabilities Inherent in COTS , 2002, ICCBSS.

[3]  Barry Boehm,et al.  About the DoD Software Tech News , 2002 .

[4]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[5]  Jyrki Kontio,et al.  A case study in applying a systematic method for COTS selection , 1996, Proceedings of IEEE 18th International Conference on Software Engineering.

[6]  M. Ochs,et al.  A method for efficient measurement-based COTS assessment and selection method description and evaluation results , 2001, Proceedings Seventh International Software Metrics Symposium.

[7]  Santiago Comella-Dorda,et al.  A Process for COTS Software Product Evaluation , 2002, ICCBSS.

[8]  Günther Ruhe,et al.  Software Engineering Decision Support ? A New Paradigm for Learning Software Organizations , 2002, LSO.

[9]  Barry Boehm,et al.  A Web Repository of Lessons Learned from COTS-Based Software Development 1 , 2002 .

[10]  Laurence Brooks,et al.  CHAPTER 53 APPLYING SOCIAL-TECHNICAL APPROACH FOR COTS SELECTION * , 1999 .

[11]  B. Phillips,et al.  Add Decision Analysis to Your COTS Selection Process , 2022 .

[12]  Efraim Turban,et al.  Decision support systems and intelligent systems , 1997 .

[13]  Cornelius Ncube,et al.  The Limitations of Current Decision-Making Techniques in the Procurement of COTS Software Components , 2002, ICCBSS.

[14]  Neil A. M. Maiden,et al.  Acquiring COTS Software Selection Requirements , 1998, IEEE Softw..

[15]  Carme Quer,et al.  Combined Selection of COTS Components , 2002, ICCBSS.

[16]  Jyrki Kontio,et al.  OTSO: a systematic process for reusable software component selection , 1995 .