From Local to Global Semantic Clone Detection

Yuan Yuan, Weiqiang Kong, Gang Hou, Yan Hu, Masahiko Watanabe, Akira Fukuda

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

Clone detection detects similar code fragments (refer to as clone code) in software products. It can help with software optimization and maintenance. Code clone detection can be divided into textual, lexical, syntactic and semantic levels. The existing technologies have achieved many good results in the first three levels, but no significant results have been obtained in semantic clone detection. In this paper, we propose a novel semantic level clone detection approach. We use the control flow graph (CFG) as an intermediate representation of the program method, combining the classical dynamic time warping (DTW) algorithm in the field of speech recognition with two deep neural network models (bidirectional RNN autoencoder and graph convolutional network (GCN)) to detect semantic level clone from local to global. We experimented with a dataset consisting of five large-scale real-world systems and a code corpus containing a large number of programming problems. The experimental results show that our approach can achieve good results in detecting both local and global semantic clone.

本文言語英語
ホスト出版物のタイトルProceedings - 2019 6th International Conference on Dependable Systems and Their Applications, DSA 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ13-24
ページ数12
ISBN(電子版)9781728160573
DOI
出版ステータス出版済み - 1 2020
イベント6th International Conference on Dependable Systems and Their Applications, DSA 2019 - Harbin, 中国
継続期間: 1 3 20201 6 2020

出版物シリーズ

名前Proceedings - 2019 6th International Conference on Dependable Systems and Their Applications, DSA 2019

会議

会議6th International Conference on Dependable Systems and Their Applications, DSA 2019
Country中国
CityHarbin
Period1/3/201/6/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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