SEHCSep 23, 2018

Which Source Code Plagiarism Detection Approach is More Humane?

arXiv:1809.08559v14 citations
Originality Incremental advance
AI Analysis

This work addresses the need for more humane plagiarism detection tools in software engineering, though it is incremental as it builds on existing approach categories.

The paper tackled the problem of aligning source code plagiarism detection with human judgment by proposing three evaluation mechanisms (think-aloud, aspect-oriented, and empirical) and comparing attribute-based and structure-based approaches. The result showed that the structure-based approach is more effective, with its signature aspect and similarity degrees better matching human preferences.

This paper contributes in developing source code plagiarism detection that is more aligned with human perspective. Three evaluation mechanisms that directly relate human perspective with evaluated approaches are proposed: think-aloud, aspect-oriented, and empirical mechanism. Using those mechanisms, a comparative study toward attribute-and structure-based plagiarism detection approach (i.e., two popular approach categories in source code plagiarism detection) is conducted. According to that study, structure-based approach is more effective than the attribute-based one; its signature aspect and resulted similarity degrees are more related to human preferences. In addition, such approach is related to most human-oriented aspects for suspecting source code plagiarism.

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