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Research Statement

By Tariq M. King

Abstract

The growing size and complexity of software systems within the last decade has led to the formulation of new development paradigms such as autonomic computing. Autonomic computing seeks to reduce the difficulties associated with managing and maintaining highly complex computing systems. In software, this is achieved by automating low-level decisions and tasks, while providing facilities for administrators to specify system behavior as high-level policies. These next-generation systems are therefore capable of dynamic self-configuration, self-optimization, self-protection, and self-healing. However, an embedded self-management infrastructure raises two interesting research questions with respect to software testing and reliability: (1) how can we be sure that autonomic changes will not introduce new errors into previously tested components?, and (2) how can we dynamically validate unforeseen interactions such as the introduction of new or adapted software components? The focus of my research is to investigate the ways in which existing software testing techniques can be tailored to provide the level of quality assurance necessary to make autonomic computing a success. In my thesis research, I have developed an integrated self-testing approach [1, 2] that monitors the behavior of autonomic components, and determines whether or not runtime testin

Year: 2012
OAI identifier: oai:CiteSeerX.psu:10.1.1.219.3986
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