A Study on Online Aspect Mining

نویسندگان

  • Yusuke Sakamoto
  • Haruhiko Sato
  • Masahito Kurihara
چکیده

In aspect-oriented programming, we can encapsulate cross-cutting concerns scattered over many modules in a system. There are many studies for detecting candidates of cross-cutting concerns called aspect mining, and automation of it. However, existing all aspect mining tools are batch processing system aiming for large systems. Compared with existing batch-type tools, this paper propose an onlinetype aspect mining tool. The online-type aspect mining tool enables us to make cross-cutting concerns aspect modules during a coding stage. Therefore, it is possible to use it also for a small-scale project which has just started.

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تاریخ انتشار 2010