Ragkhitwetsagul, C;
Krinke, J;
Marnette, B;
(2018)
A Picture Is Worth a Thousand Words: Code Clone Detection Based on Image Similarity.
In: Zou, Ying and Stephan, Matthew, (eds.)
Proceedings of 2018 IEEE 12th International Workshop on Software Clones (IWSC).
IEEE: Campobasso, Italy.
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Abstract
This paper introduces a new code clone detection technique based on image similarity. The technique captures visual perception of code seen by humans in an IDE by applying syntax highlighting and images conversion on raw source code text. We compared two similarity measures, Jaccard and earth mover’s distance (EMD) for our image-based code clone detection technique. Jaccard similarity offered better detection performance than EMD. The F1 score of our technique on detecting Java clones with pervasive code modifications is comparable to five well-known code clone detectors: CCFinderX, Deckard, iClones, NiCad, and Simian. A Gaussian blur filter is chosen as a normalisation technique for type-2 and type-3 clones. We found that blurring code images before similarity computation resulted in higher precision and recall. The detection performance after including the blur filter increased by 1 to 6 percent. The manual investigation of clone pairs in three software systems revealed that our technique, while it missed some of the true clones, could also detect additional true clone pairs missed by NiCad.
| Type: | Proceedings paper |
|---|---|
| Title: | A Picture Is Worth a Thousand Words: Code Clone Detection Based on Image Similarity |
| Event: | 12th International Workshop on Software Clones |
| Location: | Campobasso, Italy |
| Dates: | 20 March 2018 - 20 March 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/IWSC.2018.8327318 |
| Publisher version: | http://doi.org/10.1109/IWSC.2018.8327318 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10046744 |
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