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 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.

@article{El-Aziz2012,
  title     = {Clone Detection Using DIFF Algorithm For Aspect Mining},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {3},
  number    = {8},
  year      = {2012},
  publisher = {The Science and Information Organization},
  author    = {Rowyda Mohammed Abd El-Aziz and Amal Elsayed Aboutabl and Mostafa-Sami Mostafa},
  doi       = {10.14569/IJACSA.2012.030822},
  url       = {https://doi.org/10.14569/IJACSA.2012.030822}
}