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Model Driven Engineering Languages and Systems

Overview of attention for book
Cover of 'Model Driven Engineering Languages and Systems'

Table of Contents

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    Book Overview
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    Chapter 1 A Unified Approach to Modeling and Programming
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    Chapter 2 Generic Meta-modelling with Concepts, Templates and Mixin Layers
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    Chapter 3 An Observer-Based Notion of Model Inheritance
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    Chapter 4 MDE-Based Approach for Generalizing Design Space Exploration
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    Chapter 5 A Comparison of Model Migration Tools
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    Chapter 6 Incremental Evaluation of Model Queries over EMF Models
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    Chapter 7 Active Operations on Collections
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    Chapter 8 trans ML: A Family of Languages to Model Model Transformations
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    Chapter 9 Henshin: Advanced Concepts and Tools for In-Place EMF Model Transformations
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    Chapter 10 A Technique for Automatic Validation of Model Transformations
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    Chapter 11 Static- and Dynamic Consistency Analysis of UML State Chart Models
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    Chapter 12 Verifying Semantic Conformance of State Machine-to-Java Code Generators
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    Chapter 13 A Dynamic-Priority Based Approach to Fixing Inconsistent Feature Models
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    Chapter 14 Taming Graphical Modeling
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    Chapter 15 Taming EMF and GMF Using Model Transformation
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    Chapter 16 A Visual Traceability Modeling Language
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    Chapter 17 Application Logic Patterns – Reusable Elements of User-System Interaction
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    Chapter 18 A Metamodel-Based Approach for Automatic User Interface Generation
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    Chapter 19 Rapid UI Development for Enterprise Applications: Combining Manual and Model-Driven Techniques
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    Chapter 20 Environment Modeling with UML/MARTE to Support Black-Box System Testing for Real-Time Embedded Systems: Methodology and Industrial Case Studies
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    Chapter 21 Improving Test Models for Large Scale Industrial Systems: An Inquisitive Study
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    Chapter 22 Automatically Discovering Properties That Specify the Latent Behavior of UML Models
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    Chapter 23 Towards a Semantics of Activity Diagrams with Semantic Variation Points
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    Chapter 24 An AADL-Based Approach to Variability Modeling of Automotive Control Systems
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    Chapter 25 Extending Variability for OCL Interpretation
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    Chapter 26 Inter-modelling: From Theory to Practice
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    Chapter 27 Consistent Modeling Using Multiple UML Profiles
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    Chapter 28 A Systematic Review on the Definition of UML Profiles
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

8 X users
2 patents


5 Dimensions

Readers on

1 Mendeley
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Model Driven Engineering Languages and Systems
Published by
ADS, January 2010
DOI 10.1007/978-3-642-16145-2
978-3-64-216144-5, 978-3-64-216145-2

Dorina C. Petriu, Nicolas Rouquette, Øystein Haugen

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 300%
Professor > Associate Professor 2 200%
Student > Master 2 200%
Student > Bachelor 1 100%
Lecturer 1 100%
Other 0 0%
Readers by discipline Count As %
Computer Science 8 800%
Engineering 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 October 2020.
All research outputs
of 23,031,582 outputs
Outputs from ADS
of 37,458 outputs
Outputs of similar age
of 164,986 outputs
Outputs of similar age from ADS
of 795 outputs
Altmetric has tracked 23,031,582 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 37,458 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 164,986 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 795 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.