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  • 标题:Clone Detection Using DIFF Algorithm For Aspect Mining
  • 本地全文:下载
  • 作者:Rowyda Mohammed Abd El-Aziz ; Amal Elsayed Aboutabl ; Mostafa-Sami Mostafa
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2012
  • 卷号:3
  • 期号:8
  • DOI:10.14569/IJACSA.2012.030822
  • 出版社:Science and Information Society (SAI)
  • 摘要:Aspect mining is a reverse engineering process that aims at mining legacy systems to discover crosscutting concerns to be refactored into aspects. This process improves system reusability and maintainability. But, locating crosscutting concerns in legacy systems manually is very difficult and causes many errors. So, there is a need for automated techniques that can discover crosscutting concerns in source code. Aspect mining approaches are automated techniques that vary according to the type of crosscutting concerns symptoms they search for. Code duplication is one of such symptoms which risks software maintenance and evolution. So, many code clone detection techniques have been proposed to find this duplicated code in legacy systems. In this paper, we present a clone detection technique to extract exact clones from object-oriented source code using Differential File Comparison Algorithm (DIFF) to improve system reusability and maintainability which is a major objective of aspect mining.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; aspect mining; reverse engineering; clone detection; DIFF algorithm.
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