A scalable querying scheme for memory-efficient runtime models with history
Lucas Sakizloglou, Sona Ghahremani, Matthias Barkowsky, Holger Giese · 2020
Runtime models provide a snapshot of a system at runtime at a desired level of abstraction. Via a causal connection to the modeled system and by employing model-driven engineering techniques, models support schemes for runtime adaptation where data from previous snapshots facilitates more informed decisions. Although runtime models and model-based adaptation techniques have been the focus of extensive research, schemes that treat the evolution of the model over time as a first-class citizen have only lately received attention. Consequently, there is a lack of sophisticated technology for such runtime models with history.