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Information 2015, 6(4), 592-612; doi:10.3390/info6040592

Duplication Detection When Evolving Feature Models of Software Product Lines

IMS Team, SIME Laboratory, ENSIAS, Mohammed V University, Rabat 10000, Morocco
These authors contributed equally to this work.
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Academic Editor: Ahmed El Oualkadi
Received: 23 June 2015 / Revised: 6 September 2015 / Accepted: 24 September 2015 / Published: 7 October 2015
(This article belongs to the Special Issue Selected Papers from MedICT 2015)
View Full-Text   |   Download PDF [922 KB, uploaded 7 October 2015]   |  

Abstract

After the derivation of specific applications from a software product line, the applications keep evolving with respect to new customer’s requirements. In general, evolutions in most industrial projects are expressed using natural language, because it is the easiest and the most flexible way for customers to express their needs. However, the use of this means of communication has shown its limits in detecting defects, such as inconsistency and duplication, when evolving the existing models of the software product line. The aim of this paper is to transform the natural language specifications of new evolutions into a more formal representation using natural language processing. Then, an algorithm is proposed to automatically detect duplication between these specifications and the existing product line feature models. In order to instantiate the proposed solution, a tool is developed to automatize the two operations. View Full-Text
Keywords: software product line; natural language specifications; feature models; evolution; duplication; natural language processing software product line; natural language specifications; feature models; evolution; duplication; natural language processing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Khtira, A.; Benlarabi, A.; Asri, B.E. Duplication Detection When Evolving Feature Models of Software Product Lines. Information 2015, 6, 592-612.

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