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Next steps in variability management due to autonomous behaviour and runtime learning.. VaMoS, page 2:1-2:2. ACM, (2020)Modelling Uncertainty for Requirements: The Case of Surprises., , and . REW, page 287-296. IEEE, (2023)Towards an architecture integrating complex event processing and temporal graphs for service monitoring., , , , and . SAC, page 427-435. ACM, (2021)Towards an assessment grid for intelligent modeling assistance., , , , , , , , , and 1 other author(s). MoDELS (Companion), page 48:1-48:10. ACM, (2020)Modeling Autonomic Systems in the time of ML, DevOps and Microservices.. MoDELS (Companion), page 731. IEEE, (2021)Preface of the 15th International Workshop on Models@run.time'21., , and . MoDELS (Companion), page 1. IEEE, (2021)History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems., , , and . MoDELS (Companion), page 286-295. ACM, (2022)Automated Provenance Collection at Runtime as a Cross-Cutting Concern., , and . MoDELS (Companion), page 276-285. IEEE, (2023)An architectural framework for quality-driven adaptive continuous experimentation., , , , , and . RCoSE-DDrEE@ICSE, page 20-23. IEEE / ACM, (2019)ARRoW: Tool Support for Automatic Runtime Reappraisal of Weights., and . RE, page 458-461. IEEE Computer Society, (2017)