Abstract
Nowadays many companies develop and maintain families of systems, termed product lines (PL), rather than individual systems. Furthermore, due to increase in market competition and the dynamic nature of companies’ emergence, several PLs may exist under the same roof. These PLs may be independently developed taking into consideration different sets of products and requirements. Thus the developed artifacts potentially have a different and partial view of the domain. Moreover, future development and maintenance of the different PLs may require consolidating the various artifacts into a single coherent one. In this work, we present a method for constructing domain knowledge through cross PL analysis. This method uses similarity metrics, text clustering, and mining techniques in order to create domain models and recommend on improvements to the existing PLs artifacts. Preliminary results reveal that the method outcomes reflect human perception of the examined domain.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Acher, M., Cleve, A., Collet, P., Merle, P., Duchien, L., Lahire, P.: Reverse engineering architectural feature models. Software Architecture, 220–235 (2011)
Acher, M., Cleve, A., Perrouin, G., Heymans, P., Vanbeneden, C., Collet, P., Lahire, P.: On extracting feature models from product descriptions. In: Proceedings of the 6th VaMoS Workshop, pp. 45–54. ACM Press (2012)
Arango, G.: Domain analysis methods. In: Horwood, E. (ed.) Software Reusability, Chichester, England, pp. 17–49 (1994)
Choi, N., Song, I.Y., Han, H.: A survey on ontology mapping. ACM Sigmod Record 35(3), 34–41 (2006)
Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addisson-Wesley (2001)
Czarnecki, K.: Generative Programming: Methods, Techniques, and Applications Tutorial Abstract. In: Gacek, C. (ed.) ICSR-7. LNCS, vol. 2319, pp. 351–352. Springer, Heidelberg (2002)
Edmonds, J.: Optimum branchings. Journal of Research of the National Bureau of Standards – B: Mathematics and Mathematical Physics 71B(4), 233–240 (1967)
Frakes, W.B., Kang, K.: Software Reuse Research: Status and Future. IEEE Transactions on Software Engineering 31(7), 529–536 (2005)
Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55, 119–139 (1997)
Freund, Y., Schapire, R., Abe, N.: A short introduction to boosting. Journal of Japanese Society for Artificial Intelligence 14, 771–780 (1999)
Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 1606–1611 (2007)
Giachetti, G., Marín, B., Pastor, O.: Using UML as a Domain-Specific Modeling Language: A Proposal for Automatic Generation of UML Profiles. In: van Eck, P., Gordijn, J., Wieringa, R. (eds.) CAiSE 2009. LNCS, vol. 5565, pp. 110–124. Springer, Heidelberg (2009)
Kamvar, S.D., Klein, D., Manning, C.D.: Interpreting and extending classical agglomerative clustering algorithms using a model-based approach. In: Proceedings of 19th International Conference on Machine Learning, pp. 283–290 (2002)
Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-Oriented Domain Analysis (FODA) Feasibility Study, SEI Technical Report (1990)
Kurita, T.: An efficient agglomerative clustering algorithm using a heap. Pattern Recognition 24(3), 205–209 (1991)
Nejati, S., Sabetzadeh, M., Chechik, M., Easterbrook, S., Zave, P.: Matching and Merging of Statecharts Specifications. In: 29th International Conference on Software Engineering, ICSE 2007, pp. 54–64 (2007)
Rabkin, A., Katz, R.: Static extraction of program configuration options. In: 33rd International Conference on Software Engineering (ICSE), pp. 131–140 (2011)
Rasmussen, E.: Clustering algorithms. Information Retrieval: Data Structures and Algorithms, 419–442 (1992)
Reinhartz-Berger, I.: Towards Automatization of Domain Modeling. Data & Knowledge Engineering 69, 491–515 (2010)
She, S., Lotufo, R., Berger, T., Wasowski, A., Czarnecki, K.: Reverse engineering feature models. In: 33rd International Conference on Software Engineering, ICSE, pp. 461–470 (2011)
Shvaiko, P., Euzenat, J.: Ontology Matching: State of the Art and Future Challenges. IEEE Transactions on Knowledge and Data Engineering 25(1), 158–176 (2013)
S.P.L.O.T Software Product Lines Online Tools, http://www.splot-research.org/
Talukdar, P.P., Ives, Z.G., Pereira, F.: Automatically incorporating new sources in keyword search-based data integration. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pp. 387–398 (2010)
Van Deursen, A., Klint, P.: Domain-specific language design requires feature descriptions. Journal of Computing and Information Technology 10(1), 1–17 (2004)
Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., Hübner, S.: Ontology-based integration of information – a survey of existing approaches. In: IJCAI 2001 Workshop: Ontologies and Information Sharing, pp. 108–117 (2001)
Weston, N., Chitchyan, R., Rashid, A.: A framework for constructing semantically composable feature models from natural language requirements. In: Proceedings of the 13th International Software Product Line Conference, SPLC 2009, pp. 211–220 (2009)
Wikipedia. Mergers and acquisitions, http://en.wikipedia.org/wiki/Mergers_and_acquisitions
WordNet: a lexical database for English, http://wordnet.princeton.edu/
Wu, Z., Palmer, M.: In Verbs semantics and lexical selection. In: Association for Computational Linguistics, pp. 133–138 (1994)
Wulf-Hadash, O., Reinhartz-Berger, I.: Cross Product Line Feature Analysis. In: Proceedings of the 7th VaMoS Workshop, pp. 123–130. ACM Press (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wulf-Hadash, O., Reinhartz-Berger, I. (2013). Constructing Domain Knowledge through Cross Product Line Analysis. In: Nurcan, S., et al. Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2013 2013. Lecture Notes in Business Information Processing, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38484-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-38484-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38483-7
Online ISBN: 978-3-642-38484-4
eBook Packages: Computer ScienceComputer Science (R0)