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Plagiarism Detection among Source Codes using Adaptive Methods
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  • Plagiarism Detection among Source Codes using Adaptive Methods
  • Plagiarism Detection among Source Codes using Adaptive Methods
저자명
Lee. Yun-Jung,Lim. Jin-Su,Ji. Jeong-Hoon,Cho. Hwaun-Gue,Woo. Gyun
간행물명
KSII Transactions on internet and information systems : TIIS
권/호정보
2012년|6권 6호|pp.1627-1648 (22 pages)
발행정보
한국인터넷정보학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.