3 research outputs found

    Viewing functions as token sequences to highlight similarities in source code

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    International audienceThe detection of similarities in source code has applications not only in software re-engineering (to eliminate redundancies) but also in software plagiarism detection. This latter can be a challenging problem since more or less extensive edits may have been performed on the original copy: insertion or removal of useless chunks of code, rewriting of expressions, transposition of code, inlining and outlining of functions, etc. In this paper, we propose a new similarity detection technique not only based on token sequence matching but also on the factorization of the function call graphs. The factorization process merges shared chunks (factors) of codes to cope, in particular, with inlining and outlining. The resulting call graph offers a view of the similarities with their nesting relations. It is useful to infer metrics quantifying similarity at a function level

    A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges

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    Measuring and evaluating source code similarity is a fundamental software engineering activity that embraces a broad range of applications, including but not limited to code recommendation, duplicate code, plagiarism, malware, and smell detection. This paper proposes a systematic literature review and meta-analysis on code similarity measurement and evaluation techniques to shed light on the existing approaches and their characteristics in different applications. We initially found over 10000 articles by querying four digital libraries and ended up with 136 primary studies in the field. The studies were classified according to their methodology, programming languages, datasets, tools, and applications. A deep investigation reveals 80 software tools, working with eight different techniques on five application domains. Nearly 49% of the tools work on Java programs and 37% support C and C++, while there is no support for many programming languages. A noteworthy point was the existence of 12 datasets related to source code similarity measurement and duplicate codes, of which only eight datasets were publicly accessible. The lack of reliable datasets, empirical evaluations, hybrid methods, and focuses on multi-paradigm languages are the main challenges in the field. Emerging applications of code similarity measurement concentrate on the development phase in addition to the maintenance.Comment: 49 pages, 10 figures, 6 table
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