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AUTOMATED CONDITION DETECTION IN REQUIREMENTS ENGINEERING

Published online by Cambridge University Press:  19 June 2023

Alexander Elenga Gärtner ,
Dietmar Göhlich  and
Tu-Anh Fay
Alexander Elenga Gärtner*
Affiliation:
TU-Berlin; IAV GmbH
Dietmar Göhlich
Affiliation:
TU-Berlin;
Tu-Anh Fay
Affiliation:
TU-Berlin;
*
Gärtner, Alexander Elenga, IAV GmbH, Germany, [email protected]

Abstract

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In product development, it is of great importance that a complete, unambiguous, and, as far as possible, contradiction-free target system is defined. Requirements documents of complex systems can contain several thousand individual requirements, derived in an interdisciplinary manner and written in natural language by many different stakeholders. Hence, errors, in the form of contradictions, cannot be completely avoided in these documents and today they must be corrected manually with high effort.

This paper presents an important building block for automated contradiction detection and quality analysis of requirements documents. We discuss the necessary identification of conditions in requirements and the extraction of the verbal expressions associated with condition and effect, respectively. We applied and analyzed natural language processing methods based on grammatical versus machine learning models. The models have been applied to 1,861 real-world requirements. Both approaches generate promising results, with an accuracy partly over 98%. However, in structured specification texts, a grammatical model is preferable due to lower effort in preprocessing and better usability.

Keywords

RequirementsMachine learningSemantic data processingSystems Engineering (SE)Evaluation
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 707 - 716
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), 2023. Published by Cambridge University Press

References

Águeda, Cristina Puente/Olivas, José, A. (2008). Analysis, detection and classification of certain conditional sentences in text documents. ReseaerchGate.Google Scholar
Asghar, Nabiha (2016). Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey. https://doi.org/10.48550/arXiv.1605.07895.CrossRefGoogle Scholar
Bender, Beate/ Gericke, Kilian (2021). Entwickeln der Anforderungsbasis: Requirements Engineering. In: Bender, Beate/Gericke, Kilian (Eds.). Pahl/Beitz Konstruktionslehre. Berlin, Heidelberg, Springer Berlin Heidelberg, 169–209.CrossRefGoogle Scholar
Bojić, D./ Bojović, M. (2017). A Streaming Dataflow Implementation of Parallel Cocke–Younger–Kasami Parser. In: Creativity in Computing and DataFlow SuperComputing. Elsevier, 159–199.CrossRefGoogle Scholar
Bramer, Max (2013). Introduction to Classification: Naïve Bayes and Nearest Neighbour. In: Bramer, Max (Ed.). Principles of Data Mining. London, Springer London, 21–37.CrossRefGoogle Scholar
Broadbent, Alex (2008). The Difference Between Cause and Condition. Proceedings of the Aristotelian Society (Hardback) 108 (1pt3), 355–364. https://doi.org/10.1111/j.1467-9264.2008.00250.x.CrossRefGoogle Scholar
DIN 69901-5:2009-01. Project management - Project management systems - Part 5: Concepts, 2009. Berlin.Google Scholar
Duden (Ed.) (2006). Die Grammatik. Das Standardwerk zur deutschen Sprache. 7th ed. Mannheim, Dudenverl.Google Scholar
Eisenberg, Peter (2016). Duden - die Grammatik. Unentbehrlich für richtiges Deutsch. Hg. von Angelika Wöllstein. 9th ed. Berlin, Dudenverlag.Google Scholar
Ersoy, Pinar (2021). Naive Bayes Classifiers for Text Classification. Types of Naive Bayes Classifiers for Different Text Processing Cases. Available online at https://towardsdatascience.com/naive-bayes-classifiers-for-text-classification-be0d133d35ba (accessed 10/26/2022).Google Scholar
Fischbach, Jannik/Frattini, Julian/Spaans, Arjen/Kummeth, Maximilian/Vogelsang, Andreas/Mendez, Daniel/Unterkalmsteiner, Michael (2021a). Automatic Detection of Causality in Requirement Artifacts: the CiRA Approach. Available online at http://arxiv.org/pdf/2101.10766v1.CrossRefGoogle Scholar
Fischbach, Jannik/Hauptmann, Benedikt/Konwitschny, Lukas/Spies, Dominik/Vogelsang, Andreas (2020). Towards Causality Extraction from Requirements. https://doi.org/10.48550/arXiv.2006.15871.CrossRefGoogle Scholar
Fischbach, Jannik/Springer, Tobias/Frattini, Julian/Femmer, Henning/Vogelsang, Andreas/Mendez, Daniel (2021b). Fine-Grained Causality Extraction From Natural Language Requirements Using Recursive Neural Tensor Networks. Available online at http://arxiv.org/pdf/2107.09980v2.CrossRefGoogle Scholar
Frattini, Julian/Fischbach, Jannik/Mendez, Daniel/Unterkalmsteiner, Michael/Vogelsang, Andreas/Wnuk, Krzysztof (2022). Causality in requirements artifacts: prevalence, detection, and impact. Requirements Engineering. https://doi.org/10.1007/s00766-022-00371-x.CrossRefGoogle Scholar
García, Salvador/Luengo, Julián/Herrera, Francisco (2014). Data Preprocessing in Data Mining. s.l., Springer-Verlag.Google Scholar
Gärtner, Alexander Elenga (2023). condition detection. Available online at https://swarm-engineer.me/2023/condition-detection/ (accessed 2/7/2023).Google Scholar
Gärtner, Alexander Elenga/Fay, Tu-Anh/Göhlich, Dietmar (2022). Fundamental Research on Detecting Contradictions in Requirements: Taxonomy and Semi-Automated Approach. Applied Sciences 12 (15), 7628. https://doi.org/10.3390/app12157628.CrossRefGoogle Scholar
Gericke, , Kilian/Blessing, L. (2012). An analysis of design process models across disciplines. In: Marjanovic, D./Storga, M./Pavkovic, N. et al. (Eds.). DESIGN 2012. Proceedings of the 12th International Design Conference, May 21 - 24, 2012, Dubrovnik, Croatia. Zagreb, Fac. of Mechanical Engineering and Naval Architecture, pp. 171–180.Google Scholar
Göhlich, Dietmar/Bender, Beate/Fay, Tu-Anh/Gericke, Kilian (2021). PRODUCT REQUIREMENTS SPECIFICATION PROCESS IN PRODUCT DEVELOPMENT. Proceedings of the Design Society 1, 2459–2470. https://doi.org/10.1017/pds.2021.507.CrossRefGoogle Scholar
Göhlich, Dietmar/Fay, Tu-Anh/Jefferies, Dominic/Lauth, Enrico/Kunith, Alexander/Zhang, Xudong (2018). Design of urban electric bus systems. Design Science 4. https://doi.org/10.1017/dsj.2018.10.CrossRefGoogle Scholar
Gudivada, Venkat N. (2018). Natural Language Core Tasks and Applications. In: Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications. Elsevier, 403–428.Google Scholar
KHOO, C. S. G./KORNFILT, J./ODDY, R. N./MYAENG, S. H. (1998). Automatic Extraction of Cause-Effect Information from Newspaper Text Without Knowledge-based Inferencing. Literary and Linguistic Computing 13 (4), 177–186. https://doi.org/10.1093/llc/13.4.177.CrossRefGoogle Scholar
Liu, Chun/Zhao, Zhengyi/Zhang, Lei/Li, Zheng (2021). Automated Conditional Statements Checking for Complete Natural Language Requirements Specification. Applied Sciences 11 (17), 7892. https://doi.org/10.3390/app11177892.CrossRefGoogle Scholar
Loucopoulos, Pericles (2005). Requirements engineering. In: Clarkson, John/Eckert, Claudia (Eds.). Design process improvement. London, Springer London, 116–139.CrossRefGoogle Scholar
Maxwell, Joseph (1992). Understanding and Validity in Qualitative Research. Harvard Educational Review 62 (3), 279–301. https://doi.org/10.17763/haer.62.3.8323320856251826.CrossRefGoogle Scholar
Merriam-Webster (2022). condition. Available online at https://www.merriam-webster.com/dictionary/condition (accessed 10/4/2022).Google Scholar
Narkhedem, Sarang (2018). Understanding Confusion Matrix. Available online at https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62 (accessed 10/11/2022).Google Scholar
Pohl, Klaus/Rupp, Chris (2021). Basiswissen Requirements Engineering. Aus- und Weiterbildung nach IREB-Standard zum Certified Professional for Requirements Engineering Foundation Level. 5th ed. Heidelberg, dpunkt.verlag.Google Scholar
Sennrich, Rico/Volk, Martin/Schneider, Gerold (2013). Exploiting Synergies Between Open Resources for German Dependency Parsing, POS-tagging, and Morphological Analysis 2013.Google Scholar
Twain, Mark (1880). The Awful German Language. In: Mark Twain: A Tramp Abroad. Toronto, Belford & Co., 879–897.Google Scholar
VDI 2221 Blatt 1:2019-11. Design of technical products and systems - Model of product design, 2019. Berlin.Google Scholar