Code clone detection and analysis using software metrics and neural network: A Literature Review

Abstract

Code clones are the duplicated code which degrade the software quality and hence increase the maintenance cost. Detection of clones in a large software system is very tedious tasks but it is necessary to improve the design, structure and quality of the software products. Object oriented metrics like DIT, NOC, WMC, LCOM, Cyclomatic complexity and various types of methods and variables are the good indicator of code clone. Artificial neural network has immense detection and prediction capability. In this paper, various types of metric based clone detection approach and techniques are discussed. From the discussion it is concluded that clone detection using software metrics and artificial neural network is the best technique of code clone detection, analysis and clone prediction