Enhancing NL Requirements Formalisation Using a Quality Checking Model

Abstract

The formalisation of natural language (NL) requirements is a challenging problem because NL is inherently vague and imprecise. Existing formalisation approaches only support requirements adhering to specific boilerplates or templates, and are affected by the requirements quality issues. Several quality models are developed to assess the quality of NL requirements. However, they do not focus on the quality issues affecting the formalisability of requirements. Such issues can greatly compromise the operation of complex systems and even lead to catastrophic consequences or loss of life (in case of critical systems). In this paper, we propose a requirements quality checking approach utilising natural language processing (NLP) analysis. The approach assesses the quality of the requirements against a quality model that we developed to enhance the formalisability of NL requirements. We evaluate the effectiveness of our approach by comparing the formalisation efficiency of a recent automatic formalisation technique before and after utilising our approach. The results show an increase of approximately 15% in the F-measure (from 83.8% to 98%).