A Context-Aware Software Adaptation Framework

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There is an increasing demand for software systems that dynamically adapt their behavior at runtime in response to changes. Research into these systems has been conducted by researchers from two communities with two different emphases: self-adaptivity and context-awareness. On one hand, research in context-awareness is more concerned with how to model, process, and manage the context information but limited on how a system adapts itself in response to unanticipated changes in the context information. On the other hand, research in self-adaptivity is more about how to adapt the system's structure and/or behavior in response to requirements and/or context changes (possibly unanticipated changes), with less attention to how context is modeled, processed, and managed. In practice, the line between the two is rather blurred, and the engineering of a context-aware adaptive system needs to consider both aspects in a systematic manner. The objective of this research project is to investigate, design, and develop a novel framework to identify the requirements of considering context-awareness and self-adaptivity in an integrated manner. First, the framework provides a novel context modeling technique that captures all the system environment aspects and supports later adaptation and evolution during the software execution; second it maintains multiple system models (i.e. the structure, behavior and quality models) and their consistency at runtime, and enables system runtime evolution; and third it provides adaptation mechanisms that can cope with unanticipated environment changes using the system-context relationships. We believe that the benefit of this project to the targeted sectors of the economy is twofold. First, it provides a superior context-aware framework that will help to develop and implement sophisticated algorithms and methods for system runtime adaptivity. Second, we believe the particular modeling techniques we aim at developing for adaptive applications will help industrial companies to effectively employ methods so that the adaptive systems can be kept up-to-date during their evolution and maintenance.