Mining Aspects in Requirements

Abstract

early identification and documentation of crosscutting concerns enables better change management and traceability of requirements. Moreover, this also improves the early identification of candidate aspects in the design and implementation stages. Current techniques for identifying aspects in requirements are ineffective when requirements are complex or unstructured. This paper describes an approach that utilises corpus-based natural language processing (NLP) techniques to effectively enable the identification of aspects in a semi-automated way. The technique proposed here describes how unstructured sources of requirements (e.g., interviews, natural language description of the system) or requirements documents can be automatically mined to help the requirements engineer quickly identify and build a structured