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Authors: Amal Khtira ; Anissa Benlarabi and Bouchra El Asri

Affiliation: Mohammed V University, Morocco

ISBN: 978-989-758-100-7

Keyword(s): Natural Language Requirements, Software Product Line, Feature Duplication, Natural Language Processing.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Requirements Engineering ; Symbolic Systems

Abstract: Software product lines are dynamic systems that need to evolve continuously to meet new customer requirements. This evolution impacts both the core platform of the product line and its derived products. For several reasons, the most common way to express requirements by customers is natural language. However, the experience has shown that this communication channel does not give the possibility to detect system defects such as inconsistency and duplication. The objective of this paper is to propose a method to transform textual requirements into the XML format used by some Feature-oriented software development tools, in order to facilitate the detection of features duplication.

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Paper citation in several formats:
Khtira, A.; Benlarabi, A. and El Asri, B. (2015). Detecting Feature Duplication in Natural Language Specifications when Evolving Software Product Lines.In Proceedings of the 10th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-100-7, pages 257-262. DOI: 10.5220/0005459802570262

@conference{enase15,
author={Amal Khtira. and Anissa Benlarabi. and Bouchra El Asri.},
title={Detecting Feature Duplication in Natural Language Specifications when Evolving Software Product Lines},
booktitle={Proceedings of the 10th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2015},
pages={257-262},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005459802570262},
isbn={978-989-758-100-7},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Detecting Feature Duplication in Natural Language Specifications when Evolving Software Product Lines
SN - 978-989-758-100-7
AU - Khtira, A.
AU - Benlarabi, A.
AU - El Asri, B.
PY - 2015
SP - 257
EP - 262
DO - 10.5220/0005459802570262

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