Yanzhao Wu


2018

DOI bib
CCAligner
Pengcheng Wang, Jeffrey Svajlenko, Yanzhao Wu, Yun Xu, Chanchal K. Roy
Proceedings of the 40th International Conference on Software Engineering

Copying code and then pasting with large number of edits is a common activity in software development, and the pasted code is a kind of complicated Type-3 clone. Due to large number of edits, we consider the clone as a large-gap clone. Large-gap clone can reflect the extension of code, such as change and improvement. The existing state-of-the-art clone detectors suffer from several limitations in detecting large-gap clones. In this paper, we propose a tool, CCAligner, using code window that considers e edit distance for matching to detect large-gap clones. In our approach, a novel e-mismatch index is designed and the asymmetric similarity coefficient is used for similarity measure. We thoroughly evaluate CCAligner both for large-gap clone detection, and for general Type-1, Type-2 and Type-3 clone detection. The results show that CCAligner performs better than other competing tools in large-gap clone detection, and has the best execution time for 10MLOC input with good precision and recall in general Type-1 to Type-3 clone detection. Compared with existing state-of-the-art tools, CCAligner is the best performing large-gap clone detection tool, and remains competitive with the best clone detectors in general Type-1, Type-2 and Type-3 clone detection.