Reference : NARCIA: An Automated Tool for Change Impact Analysis in Natural Language Requirements
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/21517
NARCIA: An Automated Tool for Change Impact Analysis in Natural Language Requirements
English
Arora, Chetan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Sabetzadeh, Mehrdad mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Göknil, Arda mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Briand, Lionel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Zimmer, Frank [SES TechCom]
Sep-2015
10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, Bergamo 30 August - 4 September 2015
962-965
Yes
10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE 2015)
30-08-2015 to 4-09-2015
[en] Natural Language Requirements ; Natural Language Processing (NLP) ; Change Impact Analysis
[en] We present NARCIA, a tool for analyzing the impact of change in natural language requirements. For a given change in a requirements document, NARCIA calculates quantitative scores suggesting how likely each requirements statement in the document is to be impacted. These scores, computed using Natural Language Processing (NLP), are used for sorting the requirements statements, enabling the user to focus on statements that are most likely to be impacted. To increase the accuracy of change impact analysis, NARCIA provides a mechanism for making explicit the rationale behind changes. NARCIA has been empirically evaluated on two industrial case studies. The results of this evaluation are briefly highlighted.
http://hdl.handle.net/10993/21517

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