Monitoring the History of Runtime Models in Tempo

Description

Welcome to the homepage of InTempo, the querying approach that aims at efficient monitoring of history in Runtime Models.

For more information about the approach, see our related publications.

Project Team

Publications

  1. Lucas Sakizloglou, Sona Ghahremani, Thomas Brand, Matthias Barkowsky and Holger Giese. Towards Highly Scalable Runtime Models with History. In 15th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems. 2020.
  2. Lucas Sakizloglou, Sona Ghahremani, Matthias Barkowsky and Holger Giese. A Scalable Querying Scheme for Memory-efficient Runtime Models with History. In Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems. 2020.
  3. Lucas Sakizloglou, Matthias Barkowsky and Holger Giese. Keeping Pace with the History of Evolving Runtime Models. In Fundamental Approaches to Software Engineering, Pages 262--268, Springer International Publishing, Cham, 2021.
  4. Lucas Sakizloglou, Sona Ghahremani, Matthias Barkowsky and Holger Giese. Incremental Execution of Temporal Graph Queries over Runtime Models with History and its Applications. J. Software and Systems Modeling, 21(5). 2022.
  5. Lucas Sakizloglou. Evaluating Temporal Queries over History-aware Architectural Runtime Models. PhD Thesis, Potsdam University, 2023.

Software

  • InTempo EMF Plugin, available via the Eclipse Update Site

DSLs

  • The Events-to-Patterns (E2P) Specification Language
  • InTempo Query Language

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