Facilitating autonomic computing using reflection

Continuous evolution is a key trait of software-intensive systems. Many research projects investigate mechanisms to adapt software systems effectively in order to ease evolution. By observing its internal state and surrounding context continuously using feedback loops, an adaptive system is poten...

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Bibliographic Details
Main Author: Dawson, Dylan
Other Authors: Muller, Hausi A.
Language:English
en
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/1828/1408
Description
Summary:Continuous evolution is a key trait of software-intensive systems. Many research projects investigate mechanisms to adapt software systems effectively in order to ease evolution. By observing its internal state and surrounding context continuously using feedback loops, an adaptive system is potentially able to analyze its effectiveness by evaluating quality criteria and then self-tune to improve its operations. To be able to observe and possibly orchestrate continuous evolution of software systems in a complex and changing environment, we need to push monitoring and control of evolving systems to unprecedented levels. This thesis proposes implementing monitoring and evolution in adaptive systems using autonomic elements that rely on the reflective capabilities of the language in which the system is implemented. Such monitoring will allow a system to detect anomalous internal behaviour, and infer that changes to the operating context or environment have occurred.