An approach to rank code clones for efficient clone management

Code clone detection has been widely accepted and is being carried out at the industrial level using a number of tools. But along with clone detection, clone management also becomes an important area of research. Clone Management includes refactoring or even removal of clones and works on the resultant information obtained from the clone detection tools. This paper discusses an approach to rank the clone detection results in order to manage them easily. The idea behind the approach is to find out the maintenance overhead of the detected clones to define their criticality, which is calculated using factors like: size of code clone, MCC complexity and frequency of clone repetition. Based on the criticality of the clones, clones are later prioritized, so that the most critical ones can be refactored first and the least critical ones can be refactored later or can even be ignored.