Rule-based extraction of goal-use case models from text

Nguyen, Tuong Huan, Grundy, John and Almorsy, Mohamed 2015, Rule-based extraction of goal-use case models from text, in ESEC/FSE 2015 : Proceedings of the 10th joint European Software Engineering and Foundations of Software Engineering Conference, Association for Computer Machinery, New York, N.Y., pp. 591-601, doi: 10.1145/2786805.2786876.

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Title Rule-based extraction of goal-use case models from text
Author(s) Nguyen, Tuong Huan
Grundy, JohnORCID iD for Grundy, John orcid.org/0000-0003-4928-7076
Almorsy, MohamedORCID iD for Almorsy, Mohamed orcid.org/0000-0003-3812-9785
Conference name European Software Engineering and Foundations of Software Engineering. Conference (10th : 2015 : Bergamo, Italy)
Conference location Bergamo, Italy
Conference dates 30 Aug. - 04 Sep. 2015
Title of proceedings ESEC/FSE 2015 : Proceedings of the 10th joint European Software Engineering and Foundations of Software Engineering Conference
Editor(s) Di Nitto, Elisabetta
Harman, Mark
Heymans, Patrick
Publication date 2015
Conference series European Software Engineering and Foundations of Software Engineering Conference
Start page 591
End page 601
Total pages 11
Publisher Association for Computer Machinery
Place of publication New York, N.Y.
Keyword(s) goal-use modeling
extraction
semantic parameterization
Summary Goal and use case modeling has been recognized as a key approach for understanding and analyzing requirements. However, in practice, goals and use cases are often buried among other content in requirements specifications documents and written in unstructured styles. It is thus a time-consuming and error-prone process to identify such goals and use cases. In addition, having them embedded in natural language documents greatly limits the possibility of formally analyzing the requirements for problems. To address these issues, we have developed a novel rule-based approach to automatically extract goal and use case models from natural language requirements documents. Our approach is able to automatically categorize goals and ensure they are properly specified. We also provide automated semantic parameterization of artifact textual specifications to promote further analysis on the extracted goal-use case models. Our approach achieves 85% precision and 82% recall rates on average for model extraction and 88% accuracy for the automated parameterization.
ISBN 9781450336758
Language eng
DOI 10.1145/2786805.2786876
Field of Research 080309 Software Engineering
Socio Economic Objective 890201 Application Software Packages (excl. Computer Games)
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, Association for Computer Machinery
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084951

Document type: Conference Paper
Collection: School of Information Technology
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