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  • 标题:Aspect Mining Using Clustering and Association Rule Method
  • 本地全文:下载
  • 作者:Lili He, Hongtao Bai
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2006
  • 卷号:6
  • 期号:2A
  • 页码:247-247~251
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Aspect oriented programming offers a unique module, an aspect, to encapsulate scattered and tangled code, which makes it hopeful to solve the problem of crosscutting concerns. Identification and encapsulation of crosscutting concerns is the key problem in the migration from OO system to AO system. A novel aspect mining method which combines clustering and association rule technology is provided in this article. Clustering analysis based on the execution traces is provided to find out candidate aspects; while association rule mining based on the execution traces with ordered call is used to find out the crosscuts. Both the aspect code (advice body) and the crosscuts (pointcuts) are gotten after the above two processes, which constitute the aspect mining process. An actual application on real system provides the validity of our methods.
  • 关键词:AOP, Aspect mining, Clustering method, Association Rule Method, reverse engineering
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