Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
An approach to monitor application states for self-managing (autonomic) systems
OOPSLA '03 Companion of the 18th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Towards a taxonomy of software change: Research Articles
Journal of Software Maintenance and Evolution: Research and Practice - Unanticipated Software Evolution
Enabling adaptation of J2EE applications using components, web services and aspects
Proceedings of the 5th workshop on Adaptive and reflective middleware (ARM '06)
Self-Managed Systems: an Architectural Challenge
FOSE '07 2007 Future of Software Engineering
A framework for policy driven auto-adaptive systems using dynamic framed aspects
Transactions on Aspect-Oriented Software Development II
Self-adaptive software: Landscape and research challenges
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Adaptive software is a closed-loop system which aims at adjusting itself at runtime in different situations. Such a system needs a set of sensors to monitor attributes of itself and its operating environment. Furthermore, it requires a set of effectors in order to make changes in its entities. These changes are essential for fulfilling system's non-functional and functional requirements. Aspect-Oriented Programming (AOP) is a promising way to develop these sensors and effectors through static and dynamic composition of advices. This paper presents the experience of employing aspect composition in engineering a sample adaptive software. The main objectives are exploring the difficulties of utilizing this approach, and investigating the effectiveness of aspect-based adaptation actions. A J2EE bookstore application, TPC-W, was selected as the case study, to instrument sensors by the aid of static aspects, and effectors using dynamic aspects. The findings are promising, and encourage us to continue this line of research for more complex systems.