PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Ferrari A., Lipari G., Gnesi S., Spagnolo G. O. Pragmatic ambiguity detection in natural language requirements. In: AIRE 2014 - IEEE 1st International Workshop on Artificial Intelligence for Requirements Engineering (Karlskrona, Germany, 24-26 August 2014). Proceedings, pp. 1 - 8. IEEE, 2014.
 
 
Abstract
(English)
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.
URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6894849
DOI: 10.1109/AIRE.2014.6894849
Subject Pragmatic ambiguity detection
Natural language processing
D.2.2 Software Engineering. Design Tools and Techniques
D.2.4 Software/Program Verification


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