Quality criteria and an analysis framework for self-healing systems
Date
2010-02-23T21:35:53Z
Authors
Neti, Sangeeta
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Abstract
Autonomic computing has become more prevalent and, hence, its evaluation is becoming more important. In this thesis, we address the issue of evaluating the software architecture of self-healing applications with respect to the changes and adaptation over long periods of time. To facilitate this evaluation, we developed an analysis and reasoning framework for the architecture of self-healing systems. The reasoning framework is based on attribute-based architectural styles (ABASs) and is tailored to selected quality attributes. When an autonomic system evolves, the proposed reasoning framework can be used to re-analyze the system and verify certain quality attributes. The explicitly available relationship between architecture and quality attributes not only helps in documenting the current architecture design, but also allows developers to reuse the architectural analysis during long-term evolution when the original system designers are long gone. Hence, the proposed framework can facilitate both design and maintenance of self-healing systems.
In order to develop the analysis and reasoning framework, we identified key quality attributes for self-healing systems. We have also defined new autonomic-specific quality attributes for the self-healing systems, which includes support for detecting anomalous system behaviour, support for failure diagnosis, support for simulation of expected behaviour, support for differencing between expected and actual behaviour, and support for testing of correct behaviour. Further, we customized the ISO 9126 quality model to the quality requirements of self-healing systems, considering both traditional attributes as well as newly defined autonomic-specific attributes.
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Keywords
autonomic computing, computer architecture