A Novel Method of Clone Detection by Neural Networks

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  •   Pallavi Sharma

  •   Chetanpal Singh

Abstract

Code clone is that type of engine that helps to find duplicate code patterns find within the whole code. Programmers usually adopt code reusability task from previous few years, so that time consumption can be reduces. Code reusability can be done via replication or by just copy-paste. Code reusability leads to not writing code from scratch, just copy paste the useful part of the code. In finding of duplicated code fragment or text, plagiarism detection also work pretty well but it is not applicable to the large system in finding functional clone and also it is more time consuming even at small scale which make the detection method inappropriate. In this paper, we proposed a pattern similarity conditions on the basis of textual similarity for finding the code or text clones in the large content on the basis of SVM, Neural Network using Java coding, Neural Network and Sim Cad. This approach detects code or text clones from original one. The resultant simulation is taken place in the MATLAB environment, and it has shown that it is providing better results. The proposed algorithm performance is measured using parameters i.e. FRR, FAR and Accuracy.


Keywords: Clone Detection, Code-Fragment, Text, Textual Comparison

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How to Cite
[1]
Sharma, P. and Singh, C. 2019. A Novel Method of Clone Detection by Neural Networks. European Journal of Engineering and Technology Research. 4, 12 (Dec. 2019), 9-15. DOI:https://doi.org/10.24018/ejers.2019.4.12.1642.