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Formalising natural language specifications using a cognitive linguistic/configuration based approach

Authors :
Matt Selway
Georg Grossmann
Wolfgang Mayer
Markus Stumptner
Selway, Matt
Grossmann, Georg
Mayer, Wolfgang
Stumptner, Markus
17th IEEE International Enterprise Distributed Object Computing Conference Vancouver, Canada 9-13 September 2013
Source :
EDOC
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

This paper addresses the problem of transforming business specifications written in natural language into formal models suitable for use in information systems development. It proposes a method for transforming controlled natural language specifications based on the Semantics of Business Vocabulary and Business Rules standard. This approach is unique in combining techniques from Model-Driven Engineering (MDE), Cognitive Linguistics, and Knowledge-based Configuration, which allows the reliable semantic processing of specifications and integration with existing MDE tools to improve productivity, quality, and time-to-market in software development. The method first learns the vocabulary of the specification from glossary-like definitions then parses the rules of the specification and outputs the resulting formal SBVR model. Both aspects of the method are tested separately, with the system correctly learning 98% of the vocabulary and correctly interpreting 98% of the rules of an SBVR SE based example. Finally, the proposed method is compared to state-of-the-art approaches for creating formal models from natural language specifications, arguing that it meets the criteria necessary to fulfil the three goals of (1) shifting control of specification to non-technical business experts, (2) reducing the manual effort involved in formalising specifications, and (3) supporting business experts in creating well-formed sets of business vocabularies and rules. HighlightsA method for deep processing of natural language business specifications is proposed.The method is based on Cognitive Linguistics and Knowledge-based Configuration.The method acquires vocabulary from a business glossary and parses business rules.The vocabulary acquisition achieves an accuracy of 96%.The semantic analysis of rules achieves an accuracy of 98%.

Details

ISSN :
03064379
Volume :
54
Database :
OpenAIRE
Journal :
Information Systems
Accession number :
edsair.doi.dedup.....5fc888c5fc6bb521c06e07aacb66c893
Full Text :
https://doi.org/10.1016/j.is.2015.04.003