Model Extraction; Natural-Language Requirements; Natural Language Processing; Case Study Research
Abstract :
[en] Domain modeling is an important step in the transition from natural-language requirements to precise specifications. For large systems, building a domain model manually is laborious. Several approaches exist to assist engineers with this task, where Natural Language Processing is employed for automated extraction of domain model elements. Despite the existing approaches, important facets remain under-explored. Notably, there is limited empirical evidence about the usefulness of existing extraction rules in industry. Furthermore, important opportunities for enhancing the extraction rules are yet to be exploited. We develop a domain model extractor by bringing together existing extraction rules and proposing important enhancements. We apply our model extractor to four industrial requirements documents, reporting on the frequency of different extraction rules being applied. We conduct an expert study over one of these documents, investigating the accuracy and overall effectiveness of our domain model extractor.
Disciplines :
Computer science
Author, co-author :
Arora, Chetan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Sabetzadeh, Mehrdad ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Briand, Lionel ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Zimmer, Frank
External co-authors :
no
Language :
English
Title :
Extracting Domain Models from Natural-Language Requirements: Approach and Industrial Evaluation
Publication date :
October 2016
Event name :
19th International Conference on Model Driven Engineering Languages and Systems
Event place :
Saint-Malo, France
Event date :
October 2-7, 2016
Main work title :
19th International Conference on Model Driven Engineering Languages and Systems, Saint-Malo 2-7 October 2016
Peer reviewed :
Peer reviewed
FnR Project :
FNR6911386 - Enhancing The Automation And Accuracy Of Requirements Quality Assurance Processes Via Disciplined Use Of Natural Language, 2013 (01/09/2013-31/10/2016) - Chetan Arora
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