Facilitating autonomic computing using reflection
Date
2009-05-11T23:20:29Z
Authors
Dawson, Dylan
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Abstract
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.
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Keywords
Autonomic Computing, Reflection