Machine-learning abstractions for component-based self-optimizing systems
Author:
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10009-023-00726-x.pdf
Reference29 articles.
1. Bures, T., Gerostathopoulos, I., Hnetynka, P., Keznikl, J., Kit, M., Plasil, F.: DEECO: an ensemble-based component system. In: Proceedings of CBSE 2013, Vancouver, Canada, pp. 81–90 (2013). https://doi.org/10.1145/2465449.2465462
2. Replication package (2023). https://github.com/smartarch/ml-deeco-security-isola-journal
3. LNCS;M. Töpfer,2022
4. Al-Ali, R., Hnetynka, P., Havlik, J., Krivka, V., Heinrich, R., Seifermann, S., Walter, M., Juan-Verdejo, A.: Dynamic security rules for legacy systems. In: Proceedings of ECSA 2019 (Vol 2), Paris, France (2019). https://doi.org/10.1145/3344948.3344974
5. Bures, T., Gerostathopoulos, I., Hnetynka, P., Plasil, F., Krijt, F., Vinarek, J., Kofron, J.: A language and framework for dynamic component ensembles in smart systems. Int. J. Softw. Tools Technol. Transf. 22(4), 497–509 (2020). https://doi.org/10.1007/s10009-020-00558-z
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