Towards a Flexible and Evolvable Framework for Self-Adaptation

Lucas Provenvesi, Frank Eliassen


The growing complexity, scale and heterogeneity of software systems boosted a great deal of research in the field of self-management and self-adaptation. In general, current solutions are built as fixed frameworks, with rigid methodology, models and tools that are best suited for their target application domain but can not be easily applied in different domains. Furthermore, they lack the flexibility to let the developer make decisions on how the adaptation engine should work and do not consider the engine itself as a system subject to adaptation that can dynamically evolve.
In this work-in-progress paper we discuss the requirements of a more flexible and evolvable framework for self-adaptation.
We propose a conceptual model for realizing this framework, showing its benefits with an application scenario.

Full Text:




Hosted By Universit├Ątsbibliothek TU Berlin.