Boreas: an accurate and scalable token-based approach to code clone detection

Abstract

Detecting code clones in a program has many applications in software engineering and other related fields. In this paper, we present Boreas, an accurate and scalable token-based approach for code clone detection. Boreas introduces a novel counting-based method to define the characteristic matrices, which are able to describe the program segments distinctly and effectively for the purpose of clone detection. We conducted experiments on JDK 7 and Linux kernel 2.6.38.6 source code. Experimental results show that Boreas is able to match the detecting accuracy of a recently proposed syntactic-based tool Deckard, with the execution time reduced by more than an order of magnitude.

BibTeX

@inproceedings{Yuan-Guo:ASE12,
  author    = {Yang Yuan and
               Yao Guo},
  title     = {Boreas: an accurate and scalable token-based approach to code clone detection},
  booktitle = {ASE},
  pages     = {286--289},
  publisher = {{ACM}},
  year      = {2012},
}

Boreas: an accurate and scalable token-based approach to code clone detection

Abstract

Related papers