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Nuts and Bolts of Extracting Variability Models from Natural Language Requirements Documents

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Integrating Research and Practice in Software Engineering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 851))

Abstract

Natural language (NL) requirements documents are often ambiguous, and this is considered as a source of problems in the later interpretation of requirements. Ambiguity detection tools have been developed with the objective of improving the quality of requirement documents. However, defects as vagueness, optionality, weakness and multiplicity at requirements level can in some cases give an indication of possible variability, either in design and in implementation choices or configurability decisions. Variability information is actually the seed of the software engineering development practice aiming at building families of related systems, known as software product lines. Building on the results of previous analyses conducted on large and real word requirement documents, with QuARS NL analysis tool, we provide here a classification of the forms of ambiguity that indicate variation points, and we illustrate the practical aspects of the approach by means of a simple running example. To provide a more complete description of a line of software products, it is necessary to extrapolate, in addition to variability, also the common elements. To this end we propose here to take advantage of the capabilities of the REGICE tool to extract and cluster the glossary terms from the requirement documents. In summary, we introduce the combined application of two different NL processing tools to extract features and variability and use them to model a software product line.

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Notes

  1. 1.

    In natural language, and/or is often used to remark that the two arguments can be present together, or only one of them, so it actually express a logical or. On the other hand, the usage of or is often implicitly intended to express a logical exclusive or (corresponding to alternative features in a feature diagram).

References

  1. Ferrari, A., Dell’Orletta, F., Esuli, A., Gervasi, V., Gnesi, S.: Natural Language Requirements Processing: a 4D Vision. IEEE Softw. 34(6), 28–35 (2017)

    Article  Google Scholar 

  2. Casamayor, A., Godoy, D., Campo, M.: Mining textual requirements to assist architectural software design: a state of the art review. Artif. Intell. Rev. 38(3), 173–191 (2012)

    Article  Google Scholar 

  3. Ambriola, V., Gervasi, V.: On the systematic analysis of natural language requirements with CIRCE. Autom. Softw. Eng. 13(1), 107–167 (2006)

    Article  Google Scholar 

  4. Gnesi, S., Lami, G., Trentanni, G.: An automatic tool for the analysis of natural language requirements. Comput. Syst. Sci. Eng. 20, 1 (2005)

    Google Scholar 

  5. Mich, L., Garigliano, R.: Ambiguity measures in requirements engineering. In: Proceedings of ICS 2000 16th IFIP WCC, Beijing, China, 21–25 August 2000, pp. 39–48 (2000)

    Google Scholar 

  6. Ferrari, A., Gori, G., Rosadini, B., Trotta, I., Bacherini, S., Fantechi, A., Gnesi, S.: Detecting requirements defects with NLP patterns: an industrial experience in the railway domain. Empir. Softw. Eng. 23(6), 3684–3733 (2018)

    Article  Google Scholar 

  7. Wilson, W.M., Rosenberg, L.H., Hyatt, L.E.: Automated analysis of requirement specifications. In: Proceedings of the Nineteenth International Conference on Software Engineering (ICSE 1997), pp. 161–171 (1997)

    Google Scholar 

  8. https://www.qualicen.de/en/

  9. https://qracorp.com/

  10. Clements, P.C., Northrop, L.: Software Product Lines-Practices and Patterns. Addison-Wesley (2002)

    Google Scholar 

  11. Pohl, K., Böckle, G., van der Linden, F.: Software Product Line Engineering-Foundations, Principles, and Techniques. Springer (2005)

    Google Scholar 

  12. Bakar, N.H., Kasirun, Z.M., Salleh, N.: Feature extraction approaches from natural language requirements for reuse in software product lines: a systematic literature review. J. Syst. Softw. 106, 132–149 (2015)

    Article  Google Scholar 

  13. Fantechi, A., Ferrari, A., Gnesi, S., Semini, L.: Hacking an ambiguity detection tool to extract variation points: an experience report. In: Proceeding of the 12th International Workshop on Variability Modelling of Software-Intensive Systems, VAMOS 2018, Madrid, 2018, pp. 43–50. ACM (2018)

    Google Scholar 

  14. Itzik, N., Reinhartz-Berger, I., Wand, Y.: Variability analysis of requirements: considering behavioral differences and reflecting stakeholders perspectives. IEEE Trans. Softw. Eng. 42(7), 687–706 (2016)

    Article  Google Scholar 

  15. Fantechi, A., Gnesi, S., Semini, L.: Ambiguity defects as variation points in requirements. In: Proceeding of the 11th International Workshop on Variability Modelling of Software-intensive Systems, VAMOS ’17, pp. 13–19. ACM (2017)

    Google Scholar 

  16. Arora, C., Sabetzadeh, M., Briand, L., Zimmber, F.: Automated extraction and clustering of requirements glossary terms. IEEE Trans. Software Eng. 43(10), 918–945, ACM (2017)

    Google Scholar 

  17. Ferrari, A., Spagnolo, G.O., Dell’Orletta, F.: Mining commonalities and variabilities from natural language documents. In: Proceeding 17th International Software Product Lines Conference, SPLC, pp. 116–120 (2013)

    Google Scholar 

  18. Ferrari, A., Spagnolo, G.O., Gnesi, S., Dell’Orletta, F.: CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams. SPLC, pp. 402–410 (2015)

    Google Scholar 

  19. Li, Y., Schulze, S., Saake, G.: Reverse engineering variability from requirement documents based on probabilistic relevance and word embedding. SPLC, pp. 121–131 (2018)

    Google Scholar 

  20. Nasr, S.B, Bécan, G., Acher, M., Ferreira Filho, J.B., Sannier, N., Baudry, B., Davril, J.-M.: Automated extraction of product comparison matrices from informal product descriptions. J. Syst. Softw. 124, 82–103

    Article  Google Scholar 

  21. Bécan, G., Behjati, R., Gotlieb, A., Acher, M.: Synthesis of attributed feature models from product descriptions. 19th International Software Product Lines Conference. SPLC, pp. 1–10 (2015)

    Google Scholar 

  22. Bécan, G., Sannier, N., Acher, M., Barais, O., Blouin, A., Baudry, B.: Automating the formalization of product comparison matrices. ACM/IEEE Int. Conf. Autom. Softw. Eng., ASE, pp. 433–444 (2014)

    Google Scholar 

  23. Sannier, N., Acher, M., Baudry, B.: From comparison matrix to Variability Model: the Wikipedia case study. In: 28th IEEE/ACM International Conference on Automated Software Engineering, ASE, pp. 580–585 (2013)

    Google Scholar 

  24. Jarzabek, S., Ong, W.C., Zhang, H.: Handling variant requirements in domain modeling. J. Syst. Softw. 68(3), 171–182 (2003)

    Article  Google Scholar 

  25. Gervasi, V., Zowghi, D.: On the role of ambiguity in RE. In: Requirements Engineering: Foundation for Software Quality: 16th International Working Conference (REFSQ). LNCS, vol. 6182, pp. 248–254 (2010)

    Chapter  Google Scholar 

  26. Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) feasibility study, Tech. rep. SEI-90-TR-21 Carnegie-Mellon University Software Engineering Institute (1990)

    Google Scholar 

  27. Apel, S., Batory, D., Kästner, C., Saake, G.: Feature-Oriented Software Product Lines: Concepts and Implementation. Springer (2013)

    Google Scholar 

  28. Thüm, T., Kästner, C., Benduhn, F., Meinicke, J., Saake, G., Leich, T.: FeatureIDE: an extensible framework for feature-oriented software development. Sci. Comput. Program. 79, 70–85 (2014)

    Article  Google Scholar 

  29. Sun, J., Zhang, H., Wang, H.: Formal semantics and verification for feature modeling. In: Proceedings of the 10th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS ’05), pp. 303–312 (2005)

    Google Scholar 

  30. Fantechi, A., Ferrari, A., Gnesi, S., Semini, L.: Requirement engineering of software product lines: extracting variability using NLP. In: 26th IEEE International Requirements Engineering Conference, RE 2018, Banff, AB, Canada, Aug. 2018, pp. 418–423. IEEE Computer Society

    Google Scholar 

  31. Ramshaw, L., Marcus, M.: Text chunking using transformation-based learning. In: Armstrong, S., Church, K., Isabelle, P., Manzi, S., Tzoukermann, E., Yarowsky, D. (eds.) Natural Language Processing using Very Large Corpora, pp. 157–176, Kluwer (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università di Pisa, Pisa, Italy

    Eleonora Arganese & Laura Semini

  2. Dipartimento di Ingegneria dell’Informazione, Università di Firenze, Firenze, Italy

    Alessandro Fantechi

  3. ISTI-CNR, Pisa, Italy

    Stefania Gnesi

Authors
  1. Eleonora Arganese
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  2. Alessandro Fantechi
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  3. Stefania Gnesi
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  4. Laura Semini
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Corresponding author

Correspondence to Alessandro Fantechi .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Białystok, Poland

    Stan Jarzabek

  2. Institute of Information Technology, Lodz University of Technology, Łódź, Poland

    Aneta Poniszewska-Marańda

  3. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wrocław, Poland

    Lech Madeyski

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Arganese, E., Fantechi, A., Gnesi, S., Semini, L. (2020). Nuts and Bolts of Extracting Variability Models from Natural Language Requirements Documents. In: Jarzabek, S., Poniszewska-Marańda, A., Madeyski, L. (eds) Integrating Research and Practice in Software Engineering. Studies in Computational Intelligence, vol 851. Springer, Cham. https://doi.org/10.1007/978-3-030-26574-8_10

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