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  1. Transactions on Autonomous and Adaptive Systems (TAAS)
  2. ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 8
  3. Issue 4(Special Section on Best Papers from SEAMS 2012), January 2014
  4. Model-Driven Engineering of Self-Adaptive Software with EUREMA
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ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 11
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 10
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 9
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 8
Issue 4(Special Section on Best Papers from SEAMS 2012), January 2014
Introduction to the Special Section on Best Papers from SEAMS 2012
A Systematic Survey of Self-Protecting Software Systems
Model-Driven Engineering of Self-Adaptive Software with EUREMA
Adaptive Epidemic Dynamics in Networks: Thresholds and Control
CAAC -- An Adaptive and Proactive Access Control Approach for Emergencies in Smart Infrastructures
A Host-Based Approach for Unknown Fast-Spreading Worm Detection and Containment
Issue 3, September 2013
Issue 2, July 2013
Issue 1, April 2013
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 7
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 6
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 5
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 4
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 3
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 2
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 1

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Model-Driven Engineering of Self-Adaptive Software with EUREMA

Content Provider ACM Digital Library
Author Vogel, Thomas Giese, Holger
Copyright Year 2014
Abstract The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. The engine often describes the adaptation by runtime models representing the adaptable software and by activities such as analysis and planning that use these models. To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. A runtime megamodel is a specific model capturing runtime models and adaptation activities. In this article, we go one step further and present an executable modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops explicit at a higher level of abstraction and it enables solutions where multiple feedback loops interact or operate on top of each other and self-adaptation co-exists with offline adaptation for evolution.
Starting Page 1
Ending Page 33
Page Count 33
File Format PDF
ISSN 15564665
e-ISSN 15564703
DOI 10.1145/2555612
Volume Number 8
Issue Number 4
Journal ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-01-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Model-driven engineering Feedback loops Layered architecture Model interpreter Modeling language Models at runtime Self-adaptive software Software evolution
Content Type Text
Resource Type Article
Subject Control and Systems Engineering Software
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