Paper Title
A Systematic Review on Code Clone Detection Using Machine Learning Techniques

Abstract
Code clones in programming improvement are sorts of parts of code that should be distinguished by utilizing a clone recognition device. This paper talks about surveys on various code-clone recognition strategies, code reuse or cold cloning issues. The term "code cloning" refers towards the copying of program code. It’s the most considered normal approach to reusing source code in programming improvement. In the event that a bug is distinguished in one section of code, every one of the comparative fragments should be checked for a similar bug. Thus, this cloning system might prompt bug spread that essentially influences the upkeep cost. By taking into account this issue, code clone detection (CCD) shows up as a functioning area of exploration. Subsequently, there is areas of strength for a to research the most recent methods, patterns, and devices in the space of CCD. Consequently, in this paper, we extensively examine the most recent devices and methods used for the recognition of code clones. Subsequently, six strategies are characterized to distinguish the various kinds of clone, i.e., literary methodologies , lexical methodologies , tree - based approach , metric based approach , semantic methodologies , and/or half and half methodologies. It’s inferred that already there is existing few investigations for recognizing type I, type II, type III, and type IV clone exclusively. In any case, there’s a requirement to foster perfect methodologies with the proper device support on the whole recognize every one of the four sorts of clones. Besides, it is likewise expected to acquaint more methodologies with work on the improvement of a program dependancy graph (PDG) while managing location of the type IV clone. Keywords - ML, Code Clone Detection, CCD, AST, Code Reuse, CCD tools, code clone type