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Automatic derivation of use case diagrams from interrelated natural language requirements

Published online by Cambridge University Press:  16 May 2024

Simon Schleifer ,
Adriana Lungu ,
Benjamin Kruse ,
Sebastiaan van Putten ,
Stefan Goetz  and
Sandro Wartzack
Simon Schleifer*
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Adriana Lungu
Affiliation:
AUDI AG, Germany
Benjamin Kruse
Affiliation:
AUDI AG, Germany
Sebastiaan van Putten
Affiliation:
AUDI AG, Germany
Stefan Goetz
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Sandro Wartzack
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
*
[email protected]

Abstract

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Transferring natural language requirements to use case diagrams helps to avoid inherent ambiguities. However, this is usually a manual, time-consuming task that can be accelerated by utilizing Artificial Intelligence in terms of Natural Language Processing. Thus, this contribution proposes a conceptual framework for automatically grouping interrelated functional requirements and deriving use case diagrams by combining formerly isolated approaches. Moreover, the latter are evaluated by a qualitative potential analysis to support their future industrial application.

Keywords

requirements managementmodel-based systems engineering (MBSE)artificial intelligence (AI)natural language processing (NLP)use case diagrams
Type
Systems Engineering and Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2725 - 2734
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

References

Al-Hroob, A., Imam, A.T. and Al-Heisa, R. (2018), “The use of artificial neural networks for extracting actions and actors from requirements document”, Information and Software Technology, Vol. 101, pp. 1–15. https://doi.org/10.1016/j.infsof.2018.04.010CrossRefGoogle Scholar
Cai, J., Hao, J., Yang, H., Zhao, X. and Yang, Y. (2023), “A review on semi-supervised clustering”, Information Sciences, Vol. 632, pp. 164–200. https://doi.org/10.1016/j.ins.2023.02.088Google Scholar
Casamayor, A., Godoy, D. and Campo, M. (2012), “Functional grouping of natural language requirements for assistance in architectural software design”, Knowledge-Based Systems, Vol. 30, pp. 78–86. https://doi.org/10.1016/j.knosys.2011.12.009CrossRefGoogle Scholar
Chatterjee, R., Ahmed, A. and Anish, P.R. (2020), “Identification and Classification of Architecturally Significant Functional Requirements”, IEEE Seventh International Workshop on Artificial Intelligence for Requirements Engineering (AIRE), Zurich, Switzland, September 1, 2020, IEEE, pp. 9–17. https://doi.org/10.1109/AIRE51212.2020.00008CrossRefGoogle Scholar
Deeptimahanti, D.K. and Sanyal, R. (2011), “Semi-automatic generation of UML models from natural language requirements”, ISEC'11: Proceedings of the 4th India Software Engineering Conference, Thiruvananthapuram Kerala, India, February 24-27, 2011, Association for Computing Machinery, New York, NY, USA, pp. 165–174. https://doi.org/10.1145/1953355.1953378CrossRefGoogle Scholar
Elallaoui, M., Nafil, K. and Touahni, R. (2018), “Automatic Transformation of User Stories into UML Use Case Diagrams using NLP Techniques”, Procedia Computer Science, Vol. 130, pp. 42–49. https://doi.org/10.1016/j.procs.2018.04.010CrossRefGoogle Scholar
Ertel, W. (2017), Introduction to Artificial Intelligence, Springer International Publishing, Cham. https://doi.org/10.1007/978-3-319-58487-4CrossRefGoogle Scholar
Friedenthal, S., Moore, A. and Steiner, R. (2015), A Practical Guide to SysML: The Systems Modeling Language, Elsevier MK, Amsterdam; Boston. https://doi.org/10.1016/c2013-0-14457-1Google Scholar
Gulle, K.J., Ford, N., Ebel, P., Brokhausen, F. and Vogelsang, A. (2020), “Topic Modeling on User Stories using Word Mover's Distance”, IEEE Seventh International Workshop on Artificial Intelligence for Requirements Engineering (AIRE), Zurich, Switzland, September 1, 2020, IEEE, pp. 52–60. https://doi.org/10.1109/AIRE51212.2020.00015CrossRefGoogle Scholar
Jp, S., Menon, V.K., Soman, K. and Ojha, A.K.R. (2022), “A Non-Exclusive Multi-Class Convolutional Neural Network for the Classification of Functional Requirements in AUTOSAR Software Requirement Specification Text”, IEEE Access, Vol. 10, pp. 117707–117714. https://doi.org/10.1109/ACCESS.2022.3217752CrossRefGoogle Scholar
Kochbati, T., Li, S., Gérard, S. and Mraidha, C. (2021), “From User Stories to Models: A Machine Learning Empowered Automation”, Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development - MODELSWARD, February 8-10, 2021, SciTePress, pp. 28–40. https://doi.org/10.5220/0010197800280040Google Scholar
Lopez-Hernandez, D.A., Octavio Ocharan-Hernandez, J., Mezura-Montes, E. and Sanchez-Garcia, A.J. (2021), “Automatic Classification of Software Requirements using Artificial Neural Networks: A Systematic Literature Review”, 9th International Conference in Software Engineering Research and Innovation (CONISOFT), San Diega, CA, USA, October 25-29, 2021, IEEE, pp. 152–160. https://doi.org/10.1109/CONISOFT52520.2021.00030CrossRefGoogle Scholar
Malik, M.I., Sindhu, M.A. and Abbasi, R.A. (2023), “Extraction of use case diagram elements using natural language processing and network science”, PLoS ONE, Vol. 18 No. 6. https://doi.org/10.1371/journal.pone.0287502Google Scholar
Misra, J., Sengupta, S. and Podder, S. (2016), “Topic cohesion preserving requirements clustering”, RAISE'16: Proceedings of the 5th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, Austin, Texas, USA, May 14-22, 2016, Association for Computing Machinery, New York, NY, USA, pp. 22–28. https://doi.org/10.1145/2896995.2896998CrossRefGoogle Scholar
Nasiri, S., Rhazali, Y., Lahmer, M. and Adadi, A. (2021), “From User Stories to UML Diagrams Driven by Ontological and Production Model”, International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 12 No. 6, pp. 333–340. https://doi.org/10.14569/IJACSA.2021.0120637Google Scholar
Niu, N. and Easterbrook, S. (2008), “On-demand cluster analysis for product line functional requirements”, 12th International Software Product Line Conference, Limerick, Ireland, September 8-12, 2008, IEEE, pp. 87–96. https://doi.org/10.1109/SPLC.2008.11Google Scholar
Ott, D. (2013), “Automatic requirement categorization of large natural language specifications at Mercedes-Benz for review improvements”, Requirements Engineering: Foundation for Software Quality, Lecture Notes in Computer Science, Vol. 7830, pp. 50–64. https://doi.org/10.1007/978-3-642-37422-7_4CrossRefGoogle Scholar
Park, B.K. and Kim, Y.C. (2020), “Effort estimation approach through extracting use cases via informal requirement specifications”, Applied Sciences, Vol. 10 No. 9, https://doi.org/10.3390/app10093044Google Scholar
Pohl, K. and Rupp, C. (2021), Basiswissen Requirements Engineering: Aus- Und Weiterbildung Nach IREB-Standard Zum Certified Professional for Requirements Engineering Foundation Level, dpunkt.verlag, Heidelberg.Google Scholar
Salado, A. and Wach, P. (2019), “Constructing True Model-Based Requirements in SysML”, Systems, Vol. 7 No. 2: 19, https://doi.org/10.3390/systems7020019CrossRefGoogle Scholar
Salman, H.E., Hammad, M., Seriai, A.-D. and Al-Sbou, A. (2018), “Semantic clustering of functional requirements using agglomerative hierarchical clustering”, Information, Vol. 9 No. 9: 222. https://doi.org/10.3390/info9090222CrossRefGoogle Scholar
Sangounpao, K. and Muenchaisri, P. (2019), “Ontology-Based Naive Bayes Short Text Classification Method for a Small Dataset”, 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Toyama, Japan, July 8-11, 2019, pp. 53–58, https://doi.org/10.1109/SNPD.2019.8935711CrossRefGoogle Scholar
Settles, B. (2009), Active Learning Literature Survey, CS Technical Reports (TR1648), University of Wisconsin-Madison.Google Scholar
Sonbol, R., Rebdawi, G. and Ghneim, N. (2022), “The Use of NLP-Based Text Representation Techniques to Support Requirement Engineering Tasks: A Systematic Mapping Review”, IEEE Access, Vol. 10, pp. 62811–62830. https://doi.org/10.1109/ACCESS.2022.3182372CrossRefGoogle Scholar
Tiwari, S., Ameta, D. and Banerjee, A. (2019), “An Approach to Identify Use Case Scenarios from Textual Requirements Specification”, ISEC'19: Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference), Pune, India, February 14-16, 2019, Association for Computing Machinery, New York, pp. 1–11. https://doi.org/10.1145/3299771.3299774CrossRefGoogle Scholar
Tiwari, S., Rathore, S.S., Sagar, S. and Mirani, Y. (2020), “Identifying Use Case Elements from Textual Specification: A Preliminary Study”, IEEE 28th International Requirements Engineering Conference (RE), Zurich, Switzerland, August 31 - September 04, 2020, IEEE, pp. 410–411. https://doi.org/10.1109/RE48521.2020.00059CrossRefGoogle Scholar
Van Remmen, J.S., Horber, D., Lungu, A., Chang, F., Van Putten, S., Goetz, S. and Wartzack, S. (2023), “NATURAL LANGUAGE PROCESSING IN REQUIREMENTS ENGINEERING AND ITS CHALLENGES FOR REQUIREMENTS MODELLING IN THE ENGINEERING DESIGN DOMAIN”, Proceedings of the Design Society, Vol. 3: ICED23, pp. 2765–2774. https://doi.org/10.1017/pds.2023.277CrossRefGoogle Scholar
Vineetha, V.K. and Samuel, P. (2022), “A Multinomial Naïve Bayes Classifier for identifying Actors and Use Cases from Software Requirement Specification documents”, 2nd International Conference on Intelligent Technologies (CONIT), Hubli, India, June 24-26 2022, IEEE https://doi.org/10.1109/CONIT55038.2022.9848290CrossRefGoogle Scholar
Walden, D.D., Roedler, G.J., Forsberg, K., Hamelin, R.D., Shortell, T.M. (2015), Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, 4th edition., Wiley, Hoboken, New Jersey.Google Scholar