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Model-Driven Engineering of Self-Adaptive Software with EUREMA

Software Engineering · Submitted 17 May 2018

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim 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.

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arXiv ID1805.07353 (version 1)
Pith IDRST25FGF, Pith's permanent record of this paper and its review
CitationHolger Giese, Thomas Vogel. "Model-Driven Engineering of Self-Adaptive Software with EUREMA." arXiv:1805.07353 (2018). https://pith.science/paper/RST25FGF
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What the abstract itself states, as probabilities: claims first 0.08 · states limitation 0.06 · human participants 0.03 · controlled comparison 0.01 · randomized assignment 0.01 · states quantitative result 0.02 · compares with prior results 0.19 · mentions code or data availability 0.06.

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arXiv listing abstract v1. Results and the main claim are underlined; .

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.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. background 1.00 0.05 0.03 asserted 1.00
s1 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. background 1.00 0.06 0.03 asserted 0.64
s2 To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. background 1.00 0.05 0.04 asserted 0.99
s3 A runtime megamodel is a specific model capturing runtime models and adaptation activities. background 1.00 0.06 0.04 asserted 1.00
s4 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. contribution 1.00 0.92 0.26 asserted 1.00
s5 We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. contribution 0.86 0.91 0.10 asserted 1.00
s6 Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. method 0.85 0.53 0.11 asserted 1.00
s7 Additionally, they can be dynamically adjusted to adapt feedback loops. contribution 0.62 0.46 0.07 asserted 0.65
s8 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. interpretation 0.62 0.68 0.63 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from argument 0.95.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original 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.

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