We introduce an approach for automatic detection of performance antipatterns. The approach is based on a number of advanced monitoring and analysis techniques. The advanced analysis is used to identify relationships and patterns in the monitored data. This information is subsequently used to reconstruct a design model of the underlying system, which is loaded into a rule engine in order to identify predefined antipatterns. We give results of applying this approach to identify a number of antipatterns in two JEE applications. Finally, this work also categorises JEE antipatterns into categories based on the data needed to detect them.
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Parsons et al. (2008) studied this question.
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