Static detection of dynamic memory errors
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Pattern-based reverse-engineering of design components
Proceedings of the 21st international conference on Software engineering
Performance solutions: a practical guide to creating responsive, scalable software
Performance solutions: a practical guide to creating responsive, scalable software
Performance and scalability of EJB applications
OOPSLA '02 Proceedings of the 17th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Pinpoint: Problem Determination in Large, Dynamic Internet Services
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Bitter EJB
J2EE Antipatterns
SABER: smart analysis based error reduction
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Using runtime paths for macroanalysis
HOTOS'03 Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9
Towards quality driven exploration of model transformation spaces
Proceedings of the 14th international conference on Model driven engineering languages and systems
Systematic guidance in solving performance and scalability problems
Proceedings of the 18th international doctoral symposium on Components and architecture
Towards detecting software performance anti-patterns using classification techniques
ACM SIGSOFT Software Engineering Notes
Adaptation space exploration for service-oriented applications
Science of Computer Programming
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In this paper a framework to automatically detect design and deployment antipatterns in component based enterprise systems is presented. The approach taken monitors a running system and makes use of statistical analysis and techniques from the field of data mining to summarise the performance data collected. Performance antipatterns are detected from the summarised data using a rule-engine approach and are assessed in terms of their performance impact using performance models. Any antipatterns found are presented to the user in a diagramatic format.