Alessio Ferrari
ABSTRACT
A business subject who wishes to enter an established technological market is required to accurately analyse the features of the products of the different competitors. Such features are normally accessible through natural language (NL) brochures, or NL Web pages, which describe the products to potential customers. Building a feature model that hierarchically summarises the different features available in competing products can bring relevant benefits in market analysis. A company can easily visualise existing features, and reason about aspects that are not covered by the available solutions. However, designing a feature model starting from publicly available documents of existing products is a time consuming and error-prone task. In this paper, we present two tools, namely Commonality Mining Tool (CMT) and Feature Diagram Editor (FDE), which can jointly support the feature model definition process. CMT allows mining common and variant features from NL descriptions of existing products, by leveraging a natural language processing (NLP) approach based on contrastive analysis, which allows identifying domain-relevant terms from NL documents. FDE takes the commonalities and variabilities extracted by CMT, and renders them in a visual form. Moreover, FDE allows the graphical design and refinement of the final feature model, by means of an intuitive GUI.
- Feature extraction approaches from natural language requirements for reuse in software product lines: A systematic literature review. Journal of Systems and Software, (0):--, 2015. Available online 9 May 2015. Google Scholar
Digital Library
- M. Acher, A. Cleve, G. Perrouin, P. Heymans, C. Vanbeneden, P. Collet, and P. Lahire. On extracting feature models from product descriptions. In Proc. of VaMoS '12, pages 45--54, 2012. Google ScholarDigital Library
- V. Alves, C. Schwanninger, L. Barbosa, A. Rashid, P. Sawyer, P. Rayson, C. Pohl, and A. Rummler. An exploratory study of information retrieval techniques in domain analysis. In Proc. of SPLC '08, pages 67--76, 2008. Google ScholarDigital Library
- D. S. Batory. Feature models, grammars, and propositional formulas. In Proc. of SPLC, pages 7--20, 2005. Google ScholarDigital Library
- F. Bonin, F. Dell'Orletta, S. Montemagni, and G. Venturi. A contrastive approach to multi-word extraction from domain-specific corpora. In Proc. of LREC'10, pages 19--21, 2010.Google Scholar
- K. Chen, W. Zhang, H. Zhao, and H. Mei. An approach to constructing feature models based on requirements clustering. In Proc. of RE'05, pages 31--40, 2005. Google ScholarDigital Library
- J.-M. Davril, E. Delfosse, N. Hariri, M. Acher, J. Cleland-Huang, and P. Heymans. Feature model extraction from large collections of informal product descriptions. In Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering, pages 290--300. ACM, 2013. Google ScholarDigital Library
- F. Dell'Orletta. Ensemble system for part-of-speech tagging. In Proc. of Evalita'09, Evaluation of NLP and Speech Tools for Italian, 2009.Google Scholar
- F. Dell'Orletta, G. Venturi, A. Cimino, and S. Montemagni. T2k^2: a system for automatically extracting and organizing knowledge from texts. In N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, and S. Piperidis, editors, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), Reykjavik, Iceland, May 26-31, 2014., pages 2062--2070. European Language Resources Association (ELRA), 2014.Google Scholar
- H. Dumitru, M. Gibiec, N. Hariri, J. Cleland-Huang, B. Mobasher, C. Castro-Herrera, and M. Mirakhorli. On-demand feature recommendations derived from mining public product descriptions. In Proc. of ICSE'11, pages 181--190, 2011. Google ScholarDigital Library
- A. Ferrari, G. O. Spagnolo, and F. Dell'Orletta. Mining commonalities and variabilities from natural language documents. In 17th International Software Product Line Conference, SPLC 2013, Tokyo, Japan - August 26-30, 2013, pages 116--120, 2013. Google ScholarDigital Library
- A. Ferrari, G. O. Spagnolo, G. Martelli, and S. Menabeni. Product Line Engineering Applied to CBTC Systems Development. In Proc. of ISOLA'12, volume 7610 of LNCS, pages 216--230, 2012. Google ScholarDigital Library
- W. Frakes, R. Prieto-Diaz, and C. Fox. Dare: Domain analysis and reuse environment. Ann. Softw. Eng., 5: 125--141, Jan. 1998. Google ScholarDigital Library
- I. John. Capturing product line information from legacy user documentation. In Software Product Lines, pages 127--159. Springer, 2006.Google ScholarCross Ref
- K. C. Kang, S. G. Cohen, J. A. Hess, W. E. Novak, and A. S. Peterson. Feature-Oriented Domain Analysis (FODA) Feasibility Study. Technical report, Carnegie-Mellon University Software Engineering Institute, 1990.Google Scholar
- M. Mendonca, M. Branco, and D. Cowan. S.p.l.o.t.: Software product lines online tools. In Proceedings of the 24th ACM SIGPLAN Conference Companion on Object Oriented Programming Systems Languages and Applications, OOPSLA '09, pages 761--762. ACM, 2009. Google ScholarDigital Library
- N. Niu and S. M. Easterbrook. Extracting and modeling product line functional requirements. In Proc. of RE'08, pages 155--164, 2008. Google ScholarDigital Library
- N. Niu and S. M. Easterbrook. On-demand cluster analysis for product line functional requirements. In Proc. of SPLC'08, pages 87--96, 2008. Google ScholarDigital Library
- F. Roos-Frantz. Automated Analysis of Software Product Lines with Orthogonal Variability Models: Extending the FaMa Ecosystem. PhD thesis, University of Seville, 2012.Google Scholar
- S. Tan. Neighbor-weighted k-nearest neighbor for unbalanced text corpus. Expert Systems with Applications, 28(4):667--671, 2005. Google ScholarDigital Library
- N. Weston, R. Chitchyan, and A. Rashid. A framework for constructing semantically composable feature models from natural language requirements. In Proc. of SPLC '09, pages 211--220, 2009. Google ScholarDigital Library
Index Terms
- CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams
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