Uwe Aßmann

Dmytro Pukhkaiev, Uwe Aßmann

Efficiency of self-optimizing systems is heavily dependent on their optimization strategies, e.g., choosing exact or approximate solver. A choice of such a strategy, in turn, is influenced by numerous factors, such as re-optimization time, size of the problem, optimality constraints, etc. Exact solvers are domain-independent and can guarantee optimality but suffer from scaling, while approximate solvers offer a "good-enough" solution in exchange for a lack of generality and parameter-dependence. In this paper we discuss the trade-offs between exact and approximate optimizers for solving a quality-based software selection and hardware mapping problem from the scalability perspective. We show that even a simple heuristic can compete with thoroughly developed exact solvers under condition of an effective parameter tuning. Moreover, we discuss robustness of the obtained algorithm's configuration. Last but not least, we present a software product line for parameter tuning, which comprise the main features of this process and can serve as a platform for further research in the area of parameter tuning.

Jean Bézivin, Richard F. Paige, Uwe Aßmann et al.

Complex systems are hard to define. Nevertheless they are more and more frequently encountered. Examples include a worldwide airline traffic management system, a global telecommunication or energy infrastructure or even the whole legacy portfolio accumulated for more than thirty years in a large insurance company. There are currently few engineering methods and tools to deal with them in practice. The purpose of this Dagstuhl Perspectives Workshop on Model Engineering for Complex Systems was to study the applicability of Model Driven Engineering (MDE) to the development and management of complex systems. MDE is a software engineering field based on few simple and sound principles. Its power stems from the assumption of considering everything - engineering artefacts, manipulations of artefacts, etc - as a model. Our intuition was that MDE may provide the right level of abstraction to move the study of complex systems from an informal goal to more concrete grounds. In order to provide first evidence in support of this intuition, the workshop studied different visions and different approaches to the development and management of different kinds of complex systems. This note presents the summary of the discussions.