People:
Nelly Bencomo, Lancaster University, UK
Gordon Blair, Lancaster University, UK
Robert France, Colorado State University, USA
We use Models@run.time to extend the applicability of models and abstractions to the runtime environment. As is the case for software development models, a run-time model is often created to support reasoning. However, in contrast to development models, run-time models are used to reason about the operating environment and runtime behaviour, and thus these models must capture abstractions of runtime phenomena. Different dimensions need to be balanced, including resource-efficiency (time, memory, energy), context-dependency (time, location, platform), as well as personalization (quality-of-service specifications, profiles). The hypothesis is that because models@run.time provide meta-information for these dimensions during execution, run-time decisions can be facilitated and better automated. Thus, we anticipate this this technology will play an integral role in the management of self-adaptive systems.
Research Activities:
Collaborators:
Betty H.C. Cheng, Michigan State University, USA,
Uwe Aßmann, Technische Universität Dresden, Germany
Franck Fleury, SINTEF, Oslo, Norway
Cedric Jeanneret, Universitat Zurich, Switzerland
Contact: Nelly Bencomo at nelly@acm.org
Nelly Bencomo, Lancaster University, UK
Gordon Blair, Lancaster University, UK
Robert France, Colorado State University, USA
We use Models@run.time to extend the applicability of models and abstractions to the runtime environment. As is the case for software development models, a run-time model is often created to support reasoning. However, in contrast to development models, run-time models are used to reason about the operating environment and runtime behaviour, and thus these models must capture abstractions of runtime phenomena. Different dimensions need to be balanced, including resource-efficiency (time, memory, energy), context-dependency (time, location, platform), as well as personalization (quality-of-service specifications, profiles). The hypothesis is that because models@run.time provide meta-information for these dimensions during execution, run-time decisions can be facilitated and better automated. Thus, we anticipate this this technology will play an integral role in the management of self-adaptive systems.
Research Activities:
- Workshop Models@run.time This workshop series has been running for four years as part of the International MODELS Conferences. More info here.
- IEEE Computer special issue on models@runtime: In 2009 IEEE Computer published a special issue on this topic. The issue can be found here.
- Workshop Requirements@run.time This workshop is part of the RE Conference 2010. The information of the first edition is found at here
- Dagstuhl Seminar Models@run.time : We are also organizing a Dagstuhl Seminar on the topic. More info can be found here .
Collaborators:
Betty H.C. Cheng, Michigan State University, USA,
Uwe Aßmann, Technische Universität Dresden, Germany
Franck Fleury, SINTEF, Oslo, Norway
Cedric Jeanneret, Universitat Zurich, Switzerland
Contact: Nelly Bencomo at nelly@acm.org