Semantic WebBased Analysis of Product Line Variant Model - Volume 6 Number 1 (Feb. 2014) - IJCEE
Volume 6 Number 1 (Feb. 2014)
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IJCEE 2014 Vol.6 (1): 1-6 ISSN: 1793-8163
DOI: 10.7763/IJCEE.2014.V6.783

Semantic WebBased Analysis of Product Line Variant Model

Shamim Ripon, M. M. Piash, S. M. A. Hossain, and M. S. Uddin
Abstract—Feature diagrams are widely used to model software product line (SPL) variants. However, there is a lack of precisely defined formal notations for representing and verifying such models. Several proposals have been made in recent years to model product line features. In our earlier work we have presented a product line model to model and customize products from product specific features facilitating the very concept of reuse of common features throughout product family. However, no formal verification has been proposed for such product line model. This paper presents an approach to modeling and analyzing SPL model using semantic-web approach. We use OWL-DL to model the common and variant features in the SPL model. A reasoning tool is then used to verify the consistency of the feature configuration in the model. Such formal checking confirms and strengthens the variability model that has been presented in our earlier work. Besides, the OWL-DL representation also facilitates the search and maintenance of feature models and support knowledge sharing within a reusable engineering context.

Index Terms—Variability model, semantic web, product line, feature diagram, OWL, OWL-DL, racer.

The authors are with the Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh (e-mail: dshr@ ewubd.edu).

 

Cite:Shamim Ripon,  M. M. Piash, S. M. A. Hossain, and M. S. Uddin, "Semantic WebBased Analysis of Product Line Variant Model," International Journal of Computer and Electrical Engineering vol. 6, no.1, pp. 1-6, 2014.

General Information

ISSN: 1793-8163
Frequency: Quarterly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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