Clone Detection Using DIFF Algorithm For Aspect Mining

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...

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Bibliographic Details
Published inInternational journal of advanced computer science & applications Vol. 3; no. 8
Main Authors Mohammed, Rowyda, Elsayed, Amal, Mostafa, Mostafa-Sami
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 01.01.2012
Subjects
Algorithms
Automation
Legacy systems
Maintainability
Reproduction (copying)
Reverse engineering
Source code
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Summary: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.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2012.030822