Exploring the Taxonomy of Commits in Cyber-Physical Systems for Enhanced Error Fixes Investigation
https://doi.org/10.15514/ISPRAS-2024-36(2)-3
Abstract
Cyber-physical systems are a symbiosis of multi-level control systems that take into account the physical aspects of the functioning of target objects. Errors in such systems can be associated both with incorrect organization of the code and operation of the hardware, as well as with an incorrect understanding of physical laws and their numerical approximation. Continuing our previous work, we apply technologies for analyzing commits in git repositories of some well-known cyber-physical systems, followed by classification of messages from developers. As a result, we discuss the identified strong keywords and generalized fix messages that can reveal the main classes of bugs in these projects. The results of the work can be used in training and consulting on errors and vulnerabilities in complex systems.
About the Authors
Nikita Aleksandrovich STAROVOYTOV
Polzunov Altai State Technical University
Russian Federation
Russian Federation
Master student and assistant at the department of Applied Mathematics. Research interests: clusterization, text analysis.
Sergey Mikhailovich STAROLETOV
Polzunov Altai State Technical University
Russian Federation
Russian Federation
Cand. Sci. (Phys.-Math.), associate professor. Research interests: formal verification, model checking, cyber-physical systems, operating systems.
References
1. git. Available at: https://git-scm.com, accessed Jun. 24, 2024.
2. Otte S. Version control systems, 2009. Available at: https://api.semanticscholar.org/CorpusID:7541013, accessed Jun. 24, 2024.
3. Chacon S., Straub B. Pro git. Springer Nature, 2014.
4. Herzig K, Just S., Zeller A. It’s not a bug, it’s a feature: how misclassification impacts bug prediction. In Proc. 2013 35th international conference on software engineering (ICSE). IEEE, 2013, pp.392–401.
5. Kagdi H., Collard M. L., Maletic J. I. A survey and taxonomy of approaches for mining software repositories in the context of software evolution. Journal of software maintenance and evolution: Research and practice, vol. 19, no. 2, pp. 77–131, 2007.
6. Tian Y., Lawall J., Lo D. Identifying Linux bug fixing patches. In Proc. 2012 34th international conference on software engineering (ICSE). IEEE, 2012, pp. 386–396.
7. Lee, E. A. The past, present and future of cyber-physical systems: A focus on models. Sensors, vol. 15, no. 3, pp. 4837–4869, 2015.
8. Lee, E. A. Plato and the nerd: The creative partnership of humans and technology. MIT Press, 2017.
9. Rajkumar R., De Niz D., Klein M., Cyber-physical systems. Addison-Wesley Professional, 2016.
10. Gill H. From vision to reality: cyber-physical systems. In Proc. HCSS national workshop on new research directions for high confidence transportation CPS: automotive, aviation, and rail. Austin USA, 2008, pp. 1–29.
11. Sztipanovits J., Koutsoukos X., Karsai G., Kottenstette N., Antsaklis P., Gupta V., Goodwine B., Baras J., Wang S. Toward a science of cyber–physical system integration. Proceedings of the IEEE, vol. 100, no. 1, pp. 29–44, 2011.
12. Siddesh G.M., Deka G.C., Srinivasa K.G., Patnaik L.M., Cyber-physical systems: a computational perspective. CRC Press, 2015.
13. Rajkumar R., Lee I., Sha L., Stankovic J. Cyber-physical systems: the next computing revolution. In Proc. of the 47th design automation conference, 2010, pp. 731–736.
14. Luo Y., Xiao Y., Cheng L., Peng G., Yao D., Deep learning-based anomaly detection in cyber-physical systems: Progress and opportunities. ACM Computing Surveys (CSUR), vol. 54, no. 5, pp. 1–36, 2021.
15. ArduPilot Project. Available at: https://github.com/ArduPilot/ardupilot, accessed Jun. 24, 2024.
16. Staroletov S. Architectural software-hardware co-modeling a real-world cyber-physical system: Arduino-based ardupilot case. In Proc. 2021 30th Conference of Open Innovations Association. IEEE, 2021, pp. 267–278.
17. Scada-LTS. Available at: https://github.com/SCADA-LTS/Scada-LTS, accessed Jun. 24, 2024.
18. Modelica Standard Library. Available at: https://github.com/modelica/ModelicaStandardLibrary, accessed Jun. 24, 2024.
19. Fritzson P. Principles of object-oriented modeling and simulation with Modelica 3.3: a cyber-physical approach. John Wiley & Sons, 2014.
20. KeYmaera X, theorem Prover for Hybrid Systems. Available at: https://github.com/LS-Lab/KeYmaeraX-release, accessed Jun. 24, 2024.
21. Fulton N, Mitsch S., Quesel J.-D., M. Volp, Platzer A, KeYmaera X: An axiomatic tactical theorem prover for hybrid systems. In Proc. Automated Deduction-CADE-25: 25th International Conference on Automated Deduction, Berlin, Germany, August 1-7, 2015, Proceedings 25. Springer, 2015, pp. 527–538.
22. Quesel J.-D., Mitsch S., Loos S., Arechiga N., Platzer A. How to model and prove hybrid systems with KeYmaera: a tutorial on safety. International Journal on Software Tools for Technology Transfer, vol. 18, no. 1, pp. 67–91, 2016.
23. Staroletov S. Automatic proving of stability of the cyber-physical systems in the sense of Lyapunov with KeYmaera. In Proc. 2021 28th Conference of Open Innovations Association. IEEE, 2021, pp. 431–438.
24. Staroletov S., Schulte H., Baar T., Konyukhov I., Shilov N., Rozov A., Liakh T., Zyubin V. Modeling and verification using different notations for CPSs: The one-water-tank case study. In Proc. 2021 16th Conference on Computer Science and Intelligence Systems (FedCSIS). IEEE, 2021, pp. 485–488.
25. Bartocci E., Deshmukh J, Donze A., Fainekos G., Maler O., Nickovic D., Sankaranarayanan S. Specification-based monitoring of cyber-physical systems: a survey on theory, tools and applications. Lectures on Runtime Verification: Introductory and Advanced Topics, pp. 135–175, 2018.
26. Morgan J., O’Donnell G. E. Cyber physical process monitoring systems. Journal of Intelligent Manufacturing, vol. 29, no. 6, pp. 1317–1328, 2018.
27. Canizo M., Conde A., Charramendieta S., Minon R., Cid-Fuentes R. G., Onieva E., “Implementation of a large-scale platform for cyber-physical system real-time monitoring,” IEEE Access, vol. 7, pp. 52 455–52 466, 2019.
28. Ashibani Y., Mahmoud Q. H. Cyber physical systems security: Analysis, challenges and solutions. Computers & Security, vol. 68, pp. 81–97, 2017.
29. Lee E. A. Cyber physical systems: Design challenges. In Proc. 2008 11th IEEE international symposium on object and component-oriented real-time distributed computing (ISORC). IEEE, 2008, pp. 363–369.
30. Eichler C., Wagemann P., Schroder-Preikschat W. Genee: A benchmark generator for static analysis tools of energy-constrained cyber-physical systems. In Proc. of the 2nd Workshop on Benchmarking Cyber-Physical Systems and Internet of Things, 2019, pp. 1–6.
31. Fabarisov T., Yusupova N., Ding K., Morozov A., Janschek K. Model-based stochastic error propagation analysis for cyber-physical systems. Acta Polytechnica Hungarica, vol. 17, no. 8, pp. 15–28, 2020.
32. Lanotte R., Merro M, Munteanu A., Vigano L. A formal approach to physics-based attacks in cyber-physical systems. ACM Transactions on Privacy and Security (TOPS), vol. 23, no. 1, pp. 1– 41, 2020.
33. Tan L., Liu C., Li Z., Wang X., Zhou Y., Zhai C., Bug characteristics in open source software. Empirical software engineering, vol. 19, pp. 1665–1705, 2014.
34. Xiao G., Zheng Z., Yin B., Trivedi K. S., Du X., Cai K.-Y. An empirical study of fault triggers in the Linux operating system: An evolutionary perspective. IEEE Transactions on Reliability, vol. 68, no. 4, pp. 1356–1383, 2019.
35. Staroletov S., Starovoytov N., Golovnev N. Analyzing hot bugs in the Linux kernel by clustering fixing commit messages. Proceedings of the Institute for System Programming of the Russian Academy of Sciences, vol. 35, no. 3, pp. 215-242, 2023.
36. Hoder K., Voronkov A. Comparing unification algorithms in first-order theorem proving. In Proc. KI 2009: Advances in Artificial Intelligence: 32nd Annual German Conference on AI, Paderborn, Germany, September 15-18, 2009. Proceedings 32. Springer, 2009, pp. 435–443.
Review
For citations:
STAROVOYTOV N.A., STAROLETOV S.M. Exploring the Taxonomy of Commits in Cyber-Physical Systems for Enhanced Error Fixes Investigation. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2024;36(2):33-46. https://doi.org/10.15514/ISPRAS-2024-36(2)-3
Email this article 