Developing tool for crosscutting concern identification using NLP

Abstract

Aspect-oriented requirements engineering shows encouraging results in improving, identification, modularization and composition of crosscutting concerns. For instance, many techniques have been developed for crosscutting concern identification activity. This crucial activity is useful at the requirements level; it avoids coupling between requirements, improves traceability among requirements, eases function modularization, reduces software complexity, enhances the correctness of the software design, and most importantly it saves the cost. However, existing studies do not provide us with a clear definition of the term crosscutting concern and aspect. In terms of tools, most these techniques in the existing studies are only supported by semi-automated tool. It means human intervention is required to achieve the desired results. In this paper, we describe a tool that provides automated support for identifying crosscutting concern at the requirements level. The tool utilises natural language processing technique to reason about properties of the concerns and model their structure and relationship.