Abstract
Technical standards help software architects to identify relevant requirements and to facilitate system certification, i.e., to systematically assess whether a system meets critical requirements in fields like security, safety, or interoperability. Despite their usefulness, standards typically remain vague on how requirements should be addressed via solutions like patterns or reference architectures. Thus, software architecture design remains a time-consuming human-centered process.
In this work, we propose an approach on how to use knowledge graphs for supporting software architects in the design of complex industrial systems. We discuss how project-generic knowledge (e.g., technical standards) and project-specific knowledge like the description of a concrete system can be modeled as knowledge graph. Making the architectural knowledge, which is currently present in technical standards and other resources, machine-readable, enables the support of the software architect through expert systems and therefore, improve the quality of the overall system design. However, since architectural knowledge is currently presented in many different formats, the transformation to a uniform, machine-readable form is required. We demonstrate the applicability of our approach with a representative example of an industrial client-server architecture and outline research challenges for future work.
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References
Assal, H., Chiasson, S.: Security in the software development lifecycle. In: Proceedings of the Fourteenth USENIX Conference on Usable Privacy and Security, SOUPS 2018, pp. 281–296. USENIX Association, USA (2018)
Bader, S.R., Grangel-Gonzalez, I., Nanjappa, P., Vidal, M.-E., Maleshkova, M.: A knowledge graph for industry 4.0. In: Harth, A., et al. (eds.) ESWC 2020. LNCS, vol. 12123, pp. 465–480. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49461-2_27
Barenkamp, M., Rebstadt, J., Thomas, O.: Applications of AI in classical software engineering. AI Perspect. 2(1), 1–15 (2020). https://doi.org/10.1186/s42467-020-00005-4
Capilla, R., Jansen, A., Tang, A., Avgeriou, P., Babar, M.A.: 10 years of software architecture knowledge management: practice and future. J. Syst. Softw. 116, 191–205 (2016). https://doi.org/10.1016/j.jss.2015.08.054
Doukidis, G., Spinellis, D., Ebert, C.: Digital transformation - a primer for practitioners. IEEE Softw. 37(05), 13–21 (2020). https://doi.org/10.1109/MS.2020.2999969
Ehrlinger, L., Wöß, W.: Towards a definition of knowledge graphs. In: SEMANTiCS (Posters, Demos, SuCCESS) (2016)
Engleitner, N., Kreiner, W., Schwarz, N., Kopetzky, T., Ehrlinger, L.: Knowledge graph embeddings for news article tag recommendation (2021). https://doi.org/10.13140/RG.2.2.12602.52161
Farshidi, S., Jansen, S., van der Werf, J.M.: Capturing software architecture knowledge for pattern-driven design. J. Syst. Softw. 169, 110714 (2020). https://doi.org/10.1016/j.jss.2020.110714
Feilmayr, C., Wöß, W.: An analysis of ontologies and their success factors for application to business. Data Knowl. Eng. 101, 1–23 (2016). https://doi.org/10.1016/j.datak.2015.11.003
Han, J., Sarica, S., Shi, F., Luo, J.: Semantic networks for engineering design: state of the art and future directions. J. Mech. Des. 144(2) (2021). https://doi.org/10.1115/1.4052148
Hofmeister, C., Kruchten, P., Nord, R.L., Obbink, H., Ran, A., America, P.: A general model of software architecture design derived from five industrial approaches. J. Syst. Softw. 80(1), 106–126 (2007). https://doi.org/10.1016/j.jss.2006.05.024
Security for industrial automation and control systems - part 4–2: Technical security requirements for iacs components. Standard, International Electrotechnical Commission (2019)
International Electrotechnical Commission: Understanding standards. https://iec.ch/understanding-standards
International Organization for Standarization: Standards. https://www.iso.org/standards.html
Lukovnikov, D., Fischer, A., Lehmann, J., Auer, S.: Neural network-based question answering over knowledge graphs on word and character level. In: Proceedings of the 26th International Conference on World Wide Web, pp. 1211–1220. International World Wide Web Conferences Steering Committee (2017). https://doi.org/10.1145/3038912.3052675
Soliman, M., Wiese, M., Li, Y., Riebisch, M., Avgeriou, P.: Exploring web search engines to find architectural knowledge (2021)
Wang, L., Sun, X., Wang, J., Duan, Y., Li, B.: Construct bug knowledge graph for bug resolution. In: 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), pp. 189–191 (2017). https://doi.org/10.1109/ICSE-C.2017.102
Wang, X., He, X., Cao, Y., Liu, M., Chua, T.S.: Kgat: knowledge graph attention network for recommendation. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, pp. 950–958. Association for Computing Machinery, New York (2019). https://doi.org/10.1145/3292500.3330989
Yahya, M., Breslin, J.G., Ali, M.I.: Semantic web and knowledge graphs for industry 4.0. Appl. Sci. 11(11) (2021). https://doi.org/10.3390/app11115110
Acknowledgements
This work was supported in part by the Interreg Österreich-Bayern 2014–2020 Programme funded under Grant (AB292) and in part by the FFG BRIDGE project AK-Graph (grant no. 883718).
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Illescas, J., Buchgeher, G., Ehrlinger, L., Gabauer, D., Martinez-Gil, J. (2022). Representing Technical Standards as Knowledge Graph to Guide the Design of Industrial Systems. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2022. EUROCAST 2022. Lecture Notes in Computer Science, vol 13789. Springer, Cham. https://doi.org/10.1007/978-3-031-25312-6_71
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