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Research and Application of Code Similarity Based on Submission

Yu Lang

Abstract


With the continuous accumulation of resources, the similarity detection of code is becoming more difficult, and the difficulty of code reusing and rechecking is also increasing. In view of this problem, this paper proposes a code recommendation and check-research based on submission, which uses differential code cloning and word vector methods to find candidate code sets that are similar to incremental text, and uses feature extraction and clustering to select the most relevant codes from the candidate code sets to obtain repetitive codes. At the same time, it is recommended to programmers combined with relevance scores. Experimental results show that this method is feasible to some extent.


Keywords


Commit; Incremental Analysis; Code Similarity; Code Recommendation

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References


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DOI: https://doi.org/10.18282/jnt.v2i1.810

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