Abstract
Software Product Line Engineering (SPLE) is an approach to systematically reuse software-related artifacts among different, yet similar, software products. Previewing requirements as drivers of different development methods and activities, several studies have suggested using requirements specifications to identify and analyze commonality and variability of software products. These studies mainly employ semantic text similarity techniques. As a result, they might be limited in their ability to analyze the variability of the expected behaviors of software systems as perceived from an external point of view. Such a view is important when reaching different reuse decisions. In this paper we propose to introduce considerations which reflect the behavior of software products as manifested in requirement statements. To model these behavioral aspects of software requirements we use terms adapted from Bunge’s ontological model. The suggested approach automatically extracts the initial state, external events, and final state of software behavior. Then, variability is analyzed based on that view.
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Berry, D.M., Bucchiarone, A., Gnesi, S., Lami, G.,Trentanni, G.: A new quality model for natural language requirements specifications. In: The International Workshop on Requirements Engineering: Foundation of Software Quality, REFSQ (2006)
Bunge, M.: Treatise on Basic Philosophy. Ontology I: The Furniture of the World, vol. 3. Reidel, Boston (1977)
Bunge, M.: Treatise on Basic Philosophy. Ontology II: A World of Systems, vol. 4. Reidel, Boston (1979)
Burgess, C., Livesay, K., Lund, K.: Explorations in context space: Words, sentences, discourse. Discourse Processes 25(2-3), 211–257 (1998)
Chen, L., Babar, M.A.: A systematic review of evaluation of variability management approaches in software product lines. Information and Software Technology 53(4), 344–362 (2011)
Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addison-Wesley (2001)
Dumitru, H., Gibiec, M., Hariri, N., Cleland-Huang, J., Mobasher, B., Castro-Herrera, C., Mirakhorli, M.: On-demand feature recommendations derived from mining public product descriptions. In: 33rd IEEE International Conference on Software Engineering (ICSE 2011), pp. 181–190 (2011)
Gildea, D., Jurafsky, D.: Automatic Labeling of Semantic Roles. Computational Linguistics 28(3), 245–288 (2002)
Gomaa, W.H., Fahmy, A.A.: A Survey of Text Similarity Approaches. International Journal of Computer Applications 68(13), 13–18 (2013)
Jaring, M.: Variability engineering as an Integral Part of the Software Product Family Development Process, Ph.D. thesis, The Netherlands (2005)
Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) – feasibility study. Technical report no. CMU/SEI-90-TR-21). Carngie-Mellon University, Pittsburgh (1990)
Landauer, T.K., Foltz, P.W., Laham, D.: Introduction to Latent Semantic Analysis. Discourse Processes 25, 259–284 (1998)
Li, Y., McLean, D., Bandar, Z.A., O’Shea, J.D., Crockett, K.: Sentence Similarity Basedon Semantic Nets and Corpus Statistics. IEEE Transactions on Knowledge and Data Engineering 18(8), 1138–1150 (2006)
Malik, R., Subramaniam, V., Kaushik, S.: Automatically Selecting Answer Templates toRespond to Customer Emails. In: The International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 1659–1664 (2007)
Mani, I., Verhagen, M., Wellner, B., Lee, C.M., Pustejovsky, J.: Machine learning of temporal relations. In: The 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, pp. 753–760 (2006)
Mihalcea, R., Corley, C., Strapparava, C.: Corpus-based and knowledge-based measures of text semantic similarity. In: The 21st National Conference on Artificial Intelligence (AAAI 2006), vol. 1, pp. 775–780 (2006)
Niu, N., Easterbrook, S.: Extracting and modeling product line functional requirements. In: The 16th IEEE International Requirements Engineering Conference (RE 2008), pp. 155–164 (2008)
Raghunathan, K., Lee, H., Rangarajan, S., Chambers, N., Surdeanu, M., Jurafsky, D., Manning, C.: A Multi-Pass Sieve for Coreference Resolution. In: The conference on Empirical Methods in Natural Language Processing (EMNLP 2010), pp. 492–501 (2010)
Pohl, K., Böckle, G., van der Linden, F.: Software Product-line Engineering: Foundations, Principles, and Techniques. Springer (2005)
Reinhartz-Berger, I., Sturm, A., Wand, Y.: Comparing Functionality of Software Systems: An Ontological Approach. Data & Knowledge Engineering 87, 320–338 (2013)
Reinhartz-Berger, I., Sturm, A., Wand, Y.: External Variability of Software: Classification and Ontological Foundations. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 275–289. Springer, Heidelberg (2011)
Turney, P.D.: Mining the web for synonyms: PMI-IR versus LSA on TOEFL. In: Flach, P.A., De Raedt, L. (eds.) ECML 2001. LNCS (LNAI), vol. 2167, pp. 491–502. Springer, Heidelberg (2001)
Wand, Y., Weber, R.: On the ontological expressiveness of information systems analysis and design grammars. Information Systems Journal 3(4), 217–237 (1993)
Wand, Y., Weber, R.: An Ontological Model of an Information System. IEEE Transactions on Software Engineering 16(11), 1282–1292 (1990)
Weston, N., Chitchyan, R., Rashid, A.: A framework for constructing semantically composable feature models from natural language requirements. In: The 13th International Software Product Line Conference (SPLC 2009), pp. 211–220 (2009)
WordNet, http://wordnet.princeton.edu/
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Reinhartz-Berger, I., Itzik, N., Wand, Y. (2014). Analyzing Variability of Software Product Lines Using Semantic and Ontological Considerations. In: Jarke, M., et al. Advanced Information Systems Engineering. CAiSE 2014. Lecture Notes in Computer Science, vol 8484. Springer, Cham. https://doi.org/10.1007/978-3-319-07881-6_11
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DOI: https://doi.org/10.1007/978-3-319-07881-6_11
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