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Knowledge Map: Unified Domain Analysis (KM: UDA)

Knowledge Maps: Unified Domain Analysis (KM-UDA)

Professor Dr. Mohamed Fayad, PhD

Knowledge Maps (KMs) form the basis, core, and a strong foundation to understand any problem discipline and its solution patterns of Unified Domain Analysis (UDA). KM forms the ability to create reusable and stable pattern languages any domain analysis and design patterns. KM-UDA main idea is to allow practitioners and developers to master discipline of interest through true domain analysis, via stable patterns and an insightful methodological process. It gives practitioners and developers the necessary means and tools for a complete retrospective of the stable patterns that are pertinent to a discipline of special interest and the tidbits of advice, on how to use them to satisfy particular needs.

Intellectual merits of KM-UDA:

Knowledge Maps (KM) enable us to do a domain analysis related to any problem domain in a way this is not tied to a specific case or a specific condition, rather the domain analysis is done in a holistic and unified words sense. The core knowledge of related to any domain is recorded, thus enabling comprehensive requirement analysis. The benefits do not stop there. KM-UDA’s properties like intersection of different KMs, using remote KMs in association with the KM of any one domain under consideration lets us analyze the knowledge across various such Knowledge maps and thus multiple domains, as a whole and help us in coming up with requirements and design of any system that spans across more than one domain of application.

Any software that is architected and designed from the knowledge captured by Knowledge Maps, is done in a way that makes it highly adaptable in nature i.e. separation of concerns between functionality sets is extremely well done. Each part of the functionality can be taken out or some other can be plugged into the architecture, scaling it in whatever way it is required. A KM-UDA lets us come up with a stable core software system rather quickly which consists of the core knowledge for one or more applications as and how any application context is brought into the system. With the ability to design a generic stable core that can be reused in multiple scenarios, enables it to be suited and adapted to a change in the application context by changing just the application context specific parts (which are relatively a small percentage of the total system) of the software. All of this is possible since it is built on the foundation of Software Stability Model [1, 2, 3, and 4]. This brings along a few benefits, such as longevity, high returns on investments, configurability, customizability, high reusability of the artifacts developed and much more.

KMs’ References:

[1] Fayad, M.E., & Altman, A. (2001). Introduction to Software Stability. Communications of the ACM, 44 (9), September 2001.

[2] Fayad, M.E. (2002a). Accomplishing Software Stability. Communications of the ACM, 45 (1), January 2002.

[3] Fayad, M.E. (2002b). How to Deal with Software Stability. Communications of ACM, 45 (4), April 2002.

[4] M.E. Fayad and S. Wu, “Merging Multiple Conventional Models into One Stable Model”, Communications of the ACM, Vol. 45, No. 9, September 2002.

[5] Mahdy, A., & Fayad, M. E. (2002). A Software Stability Model Pattern. Proc. of the 9 th Conference on Pattern Language of Programs. Illinois, USA: Pattern Language of Programs.

[6] M.E. Fayad and M. Cline. “Aspects of Software Adaptability,” Communications of the ACM, Vol. 39, No. 10, October 1996, pp. 58-59

[7] A. Mahdy, M.E. Fayad, H. Hamza, and P. Tugnawat “Stable and Reusable Model-Based

Architectures” ECOOP 2002, Workshop on Model-based Software Reuse, June 2002, Malaga, Spain

[8] “Model-Based Software Reuse”, Lecture Notes in Computer Science, Springer Berlin /

Heidelberg, Volume 2548/2002, pp. 135-146

[9] M.E. Fayad. The Visualization Stable Analysis Pattern. IEEE International Conference on Information Reuse and Integration, Las Vegas, NV, August 2007

[10] M. E. Fayad, H. A. Sanchez and Shivanshu K. Singh, “Knowledge Maps – Fundamentally Modular Approach to Software Architecture, Design, Development and Deployment”, in Proceedings of the 19th International Conference on Software Engineering and Data Engineering, June 16-18, 2010, pp. 127-133.

[11] Y. Chen, H.S. Hamza, M.E. Fayad. A Framework for Developing Design Models with Analysis and Design Patterns. International Conference on Information Reuse and Integration, Las Vegas, NV, August 2005

[12] M. E. Fayad, H. A. Sanchez, S. G .K. Hegde, A. Basia, and A. Vakil. “Software Patterns, Knowledge Maps, and Domain Analysis”. Boca Raton, FL: Auerbach Publications, Taylor & Francis Catalog #: K16540, December 2014. ISBN-13: 978-1466571433

[13] D. Schmidt and M.E. Fayad. “Lessons Learned Building Reusable OO Frameworks for Distributed Software,” Communications of the ACM, Vol. 40, No. 10, October 1997, pp. 85-87.

[14] H. Hamza and M.E. Fayad. “Model-base Software Reuse Using Stable Analysis Patterns” ECOOP 2002, Workshop on Model-based Software Reuse, June 2002, Malaga, Spain

[15] M. E. Fayad. “Stable Analysis Patterns for Software and Systems” Boca Raton, FL: Auerbach Publications, Taylor & Francis Catalog #: K24627, May 2017. ISBN-13: 978-1-4987-0274-4

[16] M. E. Fayad. “Stable Design Patterns for Software and Systems” Boca Raton, FL: Auerbach Publications, Taylor & Francis Catalog #: K24656, July 2017. ISBN-13: 978-1-4987-0330-7

[17] M. E. Fayad and S. G .K. Hegde. “Software Architectures on-Demand” Boca Raton, FL: Auerbach Publications, December 2015. Under contract — In Progress

[18] Hanadi Alyafei. Contract-Generation Unified Software Engine. Masters project, SJSU, December 2013

[19] M.E. Fayad. Patterns Accessibility Engine, The Proceedings of the . IEEE International Conference on Information Reuse & Integration, Las Vegas, NV, August. 2007