Pragmatic ambiguity detection in natural language requirements
Alessio Ferrari, Giuseppe Lipari, Stefania Gnesi, Giorgio Oronzo Spagnolo · 2014
This paper presents an approach for pragmatic ambiguity detection in natural language requirements. Pragmatic ambiguities depend on the context of a requirement, which includes the background knowledge of the reader: different backgrounds can lead to different interpretations. The presented approach employs a graph-based modelling of the background knowledge of different readers, and uses a shortest-path search algorithm to model the pragmatic interpretation of a requirement. The comparison of different pragmatic interpretations is used to decide if a requirement is ambiguous or not. The paper also provides a case study on real-world requirements, where we have assessed the effectiveness of the approach.