QUARE: towards a question-answering model for requirements elicitation

Abstract

Requirements elicitation is a stakeholder-centered approach; therefore, natural language remains an effective way of documenting and validating requirements. As the scope of the software domain grows, software analysts process a higher number of requirements documents, generating delays and errors while characterizing the software domain. Natural language processing is key in such a process, allowing software analysts for speeding up the requirements elicitation process and mitigating the impact of the ambiguity and misinterpretations coming from natural-language-based requirements documents. However, natural-language-processing-based proposals for requirements elicitation are mainly focused on specific domains and still fail for understanding several requirements writing styles. In this paper, we present QUARE, a question-answering model for requirements elicitation. The QUARE model comprises a meta-ontology for requirements elicitation, easing the generation of requirements-elicitation-related questions and the initial structuration of any software domain. In addition, the QUARE model includes a named entity recognition and relation extraction system focused on requirements elicitation, allowing software analysts for processing several requirements writing styles. Although software analysts address a software domain at a time, they use the same kind of questions for identifying and characterizing requirements abstractions such as actors, concepts, and actions from a software domain. Such a process may be framed into the QUARE model workflow. We validate our proposal by using an experimental process including real-world requirements documents coming from several software domains and requirements writing styles. The QUARE model is a novel proposal aimed at supporting software analysts in the requirements elicitation process.