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Software Language Engineering

Overview of attention for book
Cover of 'Software Language Engineering'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The Field of Software Language Engineering
  3. Altmetric Badge
    Chapter 2 Model-Driven Engineering Meets Generic Language Technology
  4. Altmetric Badge
    Chapter 3 Software Language Engineering
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    Chapter 4 Neon: A Library for Language Usage Analysis
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    Chapter 5 Analyzing Rule-Based Behavioral Semantics of Visual Modeling Languages with Maude
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    Chapter 6 Parse Table Composition
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    Chapter 7 Practical Scope Recovery Using Bridge Parsing
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    Chapter 8 Generating Rewritable Abstract Syntax Trees
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    Chapter 9 Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains
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    Chapter 10 Engineering a DSL for Software Traceability
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    Chapter 11 Towards an Incremental Update Approach for Concrete Textual Syntaxes for UUID-Based Model Repositories
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    Chapter 12 A Model Engineering Approach to Tool Interoperability
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    Chapter 13 Engineering Languages for Specifying Product-Derivation Processes in Software Product Lines
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    Chapter 14 Transformation Language Integration Based on Profiles and Higher Order Transformations
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    Chapter 15 Formalization and Rule-Based Transformation of EMF Ecore-Based Models
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    Chapter 16 A Practical Evaluation of Using TXL for Model Transformation
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    Chapter 17 DeFacto : Language-Parametric Fact Extraction from Source Code
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    Chapter 18 A Case Study in Grammar Engineering
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    Chapter 19 Sudoku – A Language Description Case Study
  21. Altmetric Badge
    Chapter 20 The Java Programmer’s Phrase Book
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
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
61 Mendeley
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Title
Software Language Engineering
Published by
ADS, March 2009
DOI 10.1007/978-3-642-00434-6
ISBNs
978-3-64-200433-9, 978-3-64-200434-6
Editors

Gašević, Dragan, Lämmel, Ralf, Wyk, Eric

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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 7%
Chile 1 2%
Ecuador 1 2%
North Macedonia 1 2%
Belgium 1 2%
Denmark 1 2%
Unknown 52 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 31%
Researcher 8 13%
Student > Master 8 13%
Student > Doctoral Student 7 11%
Student > Bachelor 4 7%
Other 12 20%
Unknown 3 5%
Readers by discipline Count As %
Computer Science 45 74%
Engineering 7 11%
Business, Management and Accounting 2 3%
Earth and Planetary Sciences 1 2%
Chemical Engineering 1 2%
Other 2 3%
Unknown 3 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 October 2021.
All research outputs
#6,315,700
of 25,630,321 outputs
Outputs from ADS
#4,637
of 26,144 outputs
Outputs of similar age
#30,193
of 107,444 outputs
Outputs of similar age from ADS
#43
of 226 outputs
Altmetric has tracked 25,630,321 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 26,144 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 82% 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 107,444 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.