A framework for detecting, assessing and visualizing performance antipatterns in component based systems

ABSTRACT

Component-based enterprise systems often suffer from performance issues as a result of poor system design. In this paper, we propose a framework to automatically detect, assess and visualize poor system design, from a performance perspective, by analyzing run-time data using data mining techniques.

REFERENCES

• 1: Emmanuel Cecchet , Julie Marguerite , Willy Zwaenepoel, Performance and scalability of EJB applications, Proceedings of the 17th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications, November 04-08, 2002, Seattle, Washington, USA
• 2: Java Memory Profiler, http://www.khelekore.org/jmp/
• 3: Quest Software's Performasure, http://www.quest.com/performasure/index.asp
• 4: Performance solutions: a practical guide to creating responsive, scalable software, Addison Wesley Longman Publishing Co., Inc., Redwood City, CA, 2002
• 5: Rudolf K. Keller , Reinhard Schauer , Sébastien Robitaille , Patrick Pagé, Pattern-based reverse-engineering of design components, Proceedings of the 21st international conference on Software engineering, p.226-235, May 16-22, 1999, Los Angeles, California, United States [doi>10.1145/302405.302622]
• 6: Parsons, T. and Murphy, J. "A framework for automatically detecting and assessing performance antipatterns in component based systems using run-time analysis". The 9th International Workshop on Component Oriented Programming, part of the 18th European Conference on Object Oriented Programming. June 2004, Oslo, Norway.

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.2 Design Tools and Techniques
          Subjects: Computer-aided software engineering (CASE)

General Terms:
Design, Measurement, Performance

Keywords:
antipatterns, component-based systems (CBS), data mining, dynamic analysis, enterprise java beans (EJB)