This paper offers a first, in-breadth survey and comparison of current aspect mining tools and techniques. It focuses mainly on automated techniques that mine a program`s static or dynamic structure for candidate aspects. We present an initial comparative framework for distinguishing aspect mining techniques, and assess known techniques against this framework. The results of this assessment may serve as a roadmap to potential users of aspect mining techniques, to help them in selecting an appropriate technique. It also helps aspect mining researchers to identify remaining open research questions, possible avenues for future research, and interesting combinations of existing techniques.
A Survey of Automated Code-Level Aspect Mining Techniques
Tonella, Paolo
2007-01-01
Abstract
This paper offers a first, in-breadth survey and comparison of current aspect mining tools and techniques. It focuses mainly on automated techniques that mine a program`s static or dynamic structure for candidate aspects. We present an initial comparative framework for distinguishing aspect mining techniques, and assess known techniques against this framework. The results of this assessment may serve as a roadmap to potential users of aspect mining techniques, to help them in selecting an appropriate technique. It also helps aspect mining researchers to identify remaining open research questions, possible avenues for future research, and interesting combinations of existing techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
