Automated provenance graphs for models@run.time-Reference-Cited by-同舟云学术

Automated provenance graphs for models@run.time

Published:2020-10-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings
language:
Short-container-title:

Author:

Reynolds Owen¹,García-Domínguez Antonio¹,Bencomo Nelly¹

Affiliation:

1. Aston University, Birmingham, UK

Funder

EPSRC

Leverhulme Trust

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3417990.3419503

Reference31 articles.

1. Modeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation

2. Nelly Bencomo Sebastian Götz and Hui Song. 2019. Models@run.time: a guided tour of the state of the art and research challenges. Software & Systems Modeling (2019). 10.1007/s10270-018-00712-x Nelly Bencomo Sebastian Götz and Hui Song. 2019. Models@run.time: a guided tour of the state of the art and research challenges. Software & Systems Modeling (2019). 10.1007/s10270-018-00712-x

3. RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning

4. Requirements reflection

5. Models@ run.time

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