GMU Software Engineering <>  Seminar



Date: Mon, 11/09/2009

Time: 12 – 1pm

Location: 4201 Engineering

Food: Pizza & Soda


Title: Architectural Patterns for Decentralized Self-Adaptive Systems

Speaker: Danny Weyns <> 

Self-adaptability has been proposed as an effective approach to tackle the
increasing complexity of constructing and managing contemporary software
systems. Self-adaptability endows a system with the capability to adapt
itself to changes in its environment and user requirements. Several
researchers have argued that software architecture provides the right level
of abstraction and generality to deal with the challenges of
self-adaptability. One of the major challenges in self-adaptive systems is
dealing with distribution and decentralization. Decentralized control is
crucial for quality requirements such as openness and scalability. Over the
past 8 years, we have been studying decentralized architectures for
realizing self-adaptability based on multi-agent systems (MAS). A MAS
architecture structures the software in a number of interacting autonomous
entities (agents) that cooperatively realize the system goals. Agents
flexibly adapt their behavior and interactions to dynamics in the system or
its environment. In the course of designing and building various MAS
applications, we derived several architectural patterns that provide generic
solution schemes for recurring design problems. In this talk, I will zoom in
on a number of these patterns and illustrate them with practical examples. 

Danny Weyns is a post-doctoral researcher at the Katholieke Universiteit
Leuven, Belgium. His main research interests are in software architecture,
self-adaptive systems, multi-agent systems, and middleware for decentralized
systems. Danny is currently visiting researcher at Valoria Lab of the
Université de Bretagne-Sud, France where he works with Prof. Flavio Oquendo
on formal modeling of dynamic software architectures of decentralized


Title: Continuous Learning for Self-Adaptive Software Systems

Speaker: Jesper Andersson <> 


Recent computing trends, such as pervasiveness and mobility of systems,
increase the software complexity to a point where the software itself must
adapt at run-time. In order to meet functional and quality requirements in a
setting of ever changing conditions and constraints, self-adaptation is one
possible answer. Adaptive system design, development, and maintenance add
additional challenges for software engineers. In addition to the complexity
of static system engineering, systems must know when to adapt, where to
adapt, and how to adapt. Acquiring knowledge to answer these questions is a
challenging task and the problem becomes even more complex as the systems,
and number of conditions and constraints grow. In this talk we present and
exemplify work in progress on a dual learning process with architecture
support that combines off-line and on-line mechanisms. Off-line, the system
is simulated or subject for controlled executions. The collected information
is used to derive configuration knowledge, i.e., configuration rules. We
realize that off-line learning will never be 100% correct or complete in the
general case. We address this issue by employing on-line learning strategies
for gradually tuning/extending/replacing configuration knowledge.

Jesper Andersson is an assistant professor at Växjö University in Sweden.
His main research interests are in software architectures, end-user
programming and reuse for self adaptive systems development and self
adaptation in distributed architectures.



Sam Malek, Ph.D.

Assistant Professor

Department of Computer Science

Volgenau School of Information Technology and Engineering

George Mason University

Fairfax, VA 22030-4444 U.S.A.

Phone: +1-703-993-1677

Email: [log in to unmask]