Learning Performance Models Automatically
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-76352-7_6
Reference13 articles.
1. Binz, T., Breitenbücher, U., Kopp, O., Leymann, F.: TOSCA: portable automated deployment and management of cloud applications. In: Bouguettaya, A., Sheng, Q., Daniel, F. (eds.) Advanced Web Services, pp. 527–549. Springer, New York (2014). https://doi.org/10.1007/978-1-4614-7535-4_22
2. Brosig, F., Kounev, S., Krogmann, K.: Automated extraction of palladio component models from running enterprise java applications. In: Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools, pp. 1–10 (2009)
3. Duggan, M., Mason, K., Duggan, J., Howley, E., Barrett, E.: Predicting host CPU utilization in cloud computing using recurrent neural networks. In: 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST), pp. 67–72 (2017)
4. Eismann, S., Walter, J., von Kistowski, J., Kounev, S.: Modeling of parametric dependencies for performance prediction of component-based software systems at run-time. In: 2018 IEEE International Conference on Software Architecture (ICSA), pp. 135–13509 (2018)
5. Grohmann, J., Eismann, S., Elflein, S., Kistowski, J.V., Kounev, S., Mazkatli, M.: Detecting parametric dependencies for performance models using feature selection techniques. In: 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), pp. 309–322 (2019)
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