SMArDT modeling for automotive software testing I Drave, S Hillemacher, T Greifenberg, S Kriebel, E Kusmenko, ... Software: Practice and Experience, 2018 | 55 | 2018 |
Modeling architectures of cyber-physical systems E Kusmenko, A Roth, B Rumpe, M von Wenckstern Modelling Foundations and Applications: 13th European Conference, ECMFA 2017 …, 2017 | 39 | 2017 |
Highly-optimizing and multi-target compiler for embedded system models: C++ compiler toolchain for the component and connector language EmbeddedMontiArc E Kusmenko, B Rumpe, S Schneiders, M von Wenckstern Proceedings of the 21th ACM/IEEE International Conference on Model Driven …, 2018 | 30 | 2018 |
Modeling and training of neural processing systems E Kusmenko, S Nickels, S Pavlitskaya, B Rumpe, T Timmermanns 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering …, 2019 | 29 | 2019 |
Simulation Framework for Executing Component and Connector Models of Self-Driving Vehicles. F Grazioli, E Kusmenko, A Roth, B Rumpe, M von Wenckstern MODELS (Satellite Events), 109-115, 2017 | 27 | 2017 |
Artifact and reference models for generative machine learning frameworks and build systems A Atouani, JC Kirchhof, E Kusmenko, B Rumpe Proceedings of the 20th ACM SIGPLAN International Conference on Generative …, 2021 | 21 | 2021 |
On the Engineering of AI-Powered Systems E Kusmenko, S Pavlitskaya, B Rumpe, S Stüber | 19 | 2019 |
Modeling Deep Reinforcement Learning based Architectures for Cyber-Physical Systems N Gatto, E Kusmenko, B Rumpe Models Workshop MDE Intelligence, 2019 | 16 | 2019 |
Modeling Dynamic Architectures of Self-Adaptive Cooperative Systems. N Kaminski, E Kusmenko, B Rumpe J. Object Technol. 18 (2), 2:1-20, 2019 | 16 | 2019 |
Multi-level modeling framework for machine as a service applications based on product process resource models C Brecher, E Kusmenko, A Lindt, B Rumpe, S Storms, S Wein, ... Proceedings of the 2nd International Symposium on Computer Science and …, 2018 | 16 | 2018 |
Model-Based Development of Self-Adaptive Autonomous Vehicles using the SMARDT Methodology. S Hillemacher, S Kriebel, E Kusmenko, M Lorang, B Rumpe, A Sema, ... MODELSWARD, 163-178, 2018 | 16 | 2018 |
Simulation as a Service for Cooperative Vehicles JC Kirchhof, E Kusmenko, B Rumpe, H Zhang Models Workshop MASE, 2019 | 13 | 2019 |
Distributed simulation of cooperatively interacting vehicles C Frohn, P Ilov, S Kriebel, E Kusmenko, B Rumpe, A Ryndin 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 13 | 2018 |
Neural language models and few shot learning for systematic requirements processing in mdse V Bertram, M Boß, E Kusmenko, IH Nachmann, B Rumpe, D Trotta, ... Proceedings of the 15th ACM SIGPLAN International Conference on Software …, 2022 | 12 | 2022 |
MDE for machine learning-enabled software systems: a case study and comparison of MontiAnna & ML-Quadrat JC Kirchhof, E Kusmenko, J Ritz, B Rumpe, A Moin, A Badii, ... Proceedings of the 25th international conference on model driven engineering …, 2022 | 9 | 2022 |
Leveraging natural language processing for a consistency checking toolchain of automotive requirements V Bertram, H Kausch, E Kusmenko, H Nqiri, B Rumpe, C Venhoff 2023 IEEE 31st International Requirements Engineering Conference (RE), 212-222, 2023 | 8 | 2023 |
RapidCoop - Robuste Architektur durch geeignete Paradigmen für Kooperativ Interagierende Automobile J Dankert, C Dernehl, E Kusmenko AAET'17, 2017 | 8 | 2017 |
Dynamic data management for continuous retraining N Baumann, E Kusmenko, J Ritz, B Rumpe, MB Weber Proceedings of the 25th International Conference on Model Driven Engineering …, 2022 | 6 | 2022 |
Component-based integration of interconnected vehicle architectures AD Hellwig, S Kriebel, E Kusmenko, B Rumpe 2019 IEEE intelligent vehicles symposium (IV), 153-158, 2019 | 6 | 2019 |
Technical report on neural language models and few-shot learning for systematic requirements processing in mdse V Bertram, M Boß, E Kusmenko, IH Nachmann, B Rumpe, D Trotta, ... arXiv preprint arXiv:2211.09084, 2022 | 5 | 2022 |