Open AccessResearch and Application of Code Similarity Based on Submission
Author(s) -
Li Yu
Publication year - 2020
Publication title -
journal of networking and telecommunications
Language(s) - English
Resource type - Journals
ISSN - 2661-4065
DOI - 10.18282/jnt.v2i1.810
Subject(s) - computer science , code (set theory) , cluster analysis , similarity (geometry) , code reuse , cloning (programming) , relevance (law) , data mining , code review , reuse , information retrieval , artificial intelligence , programming language , static program analysis , software , software development , set (abstract data type) , image (mathematics) , ecology , political science , law , biology
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.