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Autonomic Computing and self-adaptive systems are a response to the increasing complexity required to cope with changing environments and varying system resources. However, the complexity of the adaptation logic itself increases with the available information in particular for distributed systems. This leads to uncertainty at runtime resulting in incompleteness in the representation of adaptation...
Modeling the reasoning component of self-adapting systems including its context is a challenging task. Context feature models used in dynamic software product lines help to capture the capabilities of a software as well as the monitored context values. This enables the possibility to add constraints between the context and system features. In this paper, we present an adaptation logic architecture...
Reusability of software artifacts reduces development time, effort, and error-proneness. Nevertheless, in the development of autonomic systems, developers often start from scratch when building a new system instead of reusing existing components. Many frameworks offer reusability on a higher level of abstraction, but neglect reusability on the lower component implementation level. In this short paper,...
Self-adaptive systems, which are highly related to Autonomic Computing, are a response to the increasing complexity and size of information systems. They are able to adapt their behavior to changes in the environment or system resources. A self-adaptive system consists of managed resources that realize functionality and an adaptation logic that controls the adaptations. So far, many research has been...
Understanding the user's requirements and intentions is important when developing pervasive applications. It helps making adaptation decisions and satisfying the user's needs. In order to do this, the user's intentions, the current situation and the options for application adaptation have to be taken into account. In this paper we extend prior work on situation modeling and specifying applications...
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