Application of the Optic-Wave Model of Semantics for Verification of Technical Documentation of Cyber-Physical Systems

The problem of ensuring the quality of technical documentation in the development of cyber-physical systems (CFS) was considered. It has been shown that inconsistencies in requirements, specifications and design solutions are one of the main causes of errors in the integration and testing stages, which is critical for the tasks of automation and management of complex technical objects. Disclosed is a method for automated verification of connectivity of technical documentation based on an optical-wave model of semantics. The novelty of the approach lies in the presentation of the document as a sequence of semantic events displayed in Minkowski space with the introduction of "semantic time" and light cones, which makes it possible to formalize causal relationships between requirements and their implementation. To quantify the quality of documentation, the following was introduced: coherence coefficient C, which characterizes structural connectivity; Coverage coverage index, which assesses the completeness of implementation; the proportion of logical breaks R; integrated quality metric Q. The method was tested on a case of 15 educational design works on mechatronics and automated control systems. A high correlation of the proposed metrics with expert assessment is shown: the Q integral metric shows a strong correlation (ρ = 0.94, p <0.001), the coverage index of Coverage requirements is ρ = 0.85 (p <0.001). ROC analysis confirmed the high diagnostic ability of the Q metric (AUC = 1.00). The proposed method can be used as an element of the CSF development quality management system to automatically review project documentation and ensure traceability of requirements.

1. Lee E. A. Cyber physical systems: Design challenges, 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC), 2008, pp. 363—369, DOI: 10.1109/ISORC.2008.25.

2. Rajkumar R. et al. Cyber-physical systems: The next computing revolution, Design Automation Conference. IEEE, 2010, pp. 731—736, DOI: 10.1145/1837274.1837461.

3. Letichevsky A. A., Letichevsky A. A. (Jr.), Skobelev V. G., Volkov V. A. Cyber-physical systems, Cybernetics and systems analysis, 2017, no. 3, pp. 3—19 (in Russian), DOI 10.1007/s10559-017-9984-9.

4. Gumzej R. Engineering Safe and Secure Cyber-Physical Systems. Springer, 2016, 132 p.

5. Meyer W., Oosthuizen R. Verification & Validation Methods for Complex AI-enabled Cyber-Physical Learning-Based Systems: A Systematic Literature Review, 2023 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, 2023, pp. 1—7, DOI: 10.1109/ICE/ITMC58018.2023.10332308.

6. Automating the conformity assessment of Cyber-Physical Systems software, FSE Companion 2025 — Companion Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering. ACM Press, 2025, pp. 1281—1284.

7. Cordeiro L. C. et al. Survey on automated symbolic verification and its application for synthesising cyber-physical systems, IET Cyber-Physical Systems: Theory & Applications, 2020, vol. 5, no. 1, pp. 1—24, DOI: 10.1049/iet-cps.2018.5006.

8. Grusho A. A. et al. Analysis of causal chains, Informatics and its applications, 2022, vol. 16, no. 2, pp. 68—74 (in Russian), DOI: 10.14357/19922264220209.

9. Mikolov T., Chen K., Corrado G., Dean J. Efficient estimation of word representations in vector space, arXiv preprint arXiv:1301.3781, 2013.

10. Devlin J. et al. BERT: Pre-training of deep bidirectional transformers for language understanding, Proceedings of NAACLHLT, 2019, pp. 4171—4186, DOI: 10.48550/arXiv.1810.04805.

11. Shapirovsky I., Shehtman V. B. Chronological Future Modality in Minkowski Spacetime, Advances in Modal Logic, 2003, vol. 4, pp. 437—459.

12. Filimonov N. B., Filimonov A. B. Situational approach in the tasks of automation of technical objects management, Mekhatronika, Avtomatizatsiya, Upravlenie, 2018, vol. 19, no. 9, pp. 563—578 (in Russian), DOI:10.17587/mau.19.563-578

13. Filimonov A. B., Filimonov N. B. Control of transfer zeros and poles in tasks of control systems synthesis. Part I. Compensation approach, Mekhatronika, Avtomatizatsiya, Upravlenie, 2020, vol. 21, no. 8, pp. 443—452 (in Russian), DOI: 10.17587/mau.21.443-452.

14. Antonov V. V., Palchevsky E. V., Rodionova L. E. Minkowski Space and Semiotics in Machine Learning: From Text Meaning to Visualization and Event Prediction, Problems of Telecommunications Engineering and Technology. Optical Technologies in Telecommunications: Proceedings of the XXVII and XXIII International Scientific and Technical Conferences, Ufa, 2025, pp. 38—42.