Paper Title
Aspect Mining Using Static Tools And Techniques

Aspect mining of code is one of the most helpful current research domains for the modularization, reusability, maintainability and extensibility of software. The scattered code appearing due to the absence of object-oriented design complicates the problem of crosscutting concerns identification. In this paper we focus on the utility of various static techniques available for aspect mining. The static and dynamic analysis of aspect mining that compares or combines two to three methods has already been discussed in literatures. But negligible work has been done on static techniques of aspects mining. In static technique code analysis refers to analyzing source code without executing it. Static analysis is generally used to find bugs and ensure conformance to coding guidelines. In Aspect Mining, Static analysis techniques are basically the search of patterns representing possible crosscutting concerns throughout the code source. As crosscutting concerns are believed to negatively affect advancement, maintainability and transparency of code. The first section of the paper covers a review of various proposed static techniques. The second section consists of its limitations and suitability in certain condition. The Third section proposes the hybrid method using cloning for a static analysis. This paper gives best clue for an organized start of research on Aspect mining techniques and help to make decision in choosing the best suitable technique among the available software tools and technique.