Crosscutting Concern Identification at Requirements Level

Abstract

An unresolved problem faced by software developers is the failure to identify and modularize certain artefacts that compose the software. It is difficult to modularize these artefacts because they are dispersed among other artefacts in the software properties. Aspects Oriented Requirements Engineering is showing encouraging results in improving identification, modularization and composition of crosscutting concerns. Identifying and documenting crosscutting concerns at the requirements-level is crucial. 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. Although the research area is still in its infancy, several techniques for crosscutting concern identification have already been developed. However, all of the techniques reviewed are based on semi-automated way whereby human intervention is required to achieve the desired results. Therefore, in this paper, a fully automated technique based on Natural Language Processing (NLP) is proposed to identify crosscutting concern at the requirements level.