A systematic literature review on the applications of recurrent neural networks in code clone research.

ABSTRACT: Code clones, referring to code fragments that are either similar or identical and are copied and pasted within software systems, have negative effects on both software quality and maintenance. The objective of this work is to systematically review and analyze recurrent neural network techniques used to detect code clones to shed light on the current techniques and offer valuable knowledge to the research community. Upon applying the review protocol, we have successfully identified 20 primary studies within this field from a total of 2099 studies. A deep investigation of these studies reveals that nine recurrent neural network techniques have been utilized for code clone detection, with a notable preference for LSTM techniques. These techniques have demonstrated their efficacy in detecting

SUBMITTER: Quradaa FH 

PROVIDER: S-EPMC10836701 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature