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Generative and Transformational Techniques in Software Engineering

Overview of attention for book
Cover of 'Generative and Transformational Techniques in Software Engineering'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 A Tutorial on Feature Oriented Programming and the AHEAD Tool Suite
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    Chapter 2 Generative and Transformational Techniques in Software Engineering
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    Chapter 3 Program Transformation with Reflection and Aspect-Oriented Programming
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    Chapter 4 The Transformational Approach to Database Engineering
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    Chapter 5 Program Optimizations and Transformations in Calculation Form
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    Chapter 6 Mappings Make Data Processing Go ’Round
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    Chapter 7 On the Use of Graph Transformations for Model Refactoring
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    Chapter 8 Forms2Net – Migrating Oracle Forms to Microsoft .NET
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    Chapter 9 Applications of the Asf + Sdf Meta-Environment
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    Chapter 10 MetaBorg in Action: Examples of Domain-Specific Language Embedding and Assimilation Using Stratego/XT
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    Chapter 11 Agile Parsing to Transform Web Applications
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    Chapter 12 Data Cleaning and Transformation Using the AJAX Framework
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    Chapter 13 Developing Tools with Fujaba XProM
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    Chapter 14 The COMPOST, COMPASS, Inject/J and RECODER Tool Suite for Invasive Software Composition: Invasive Composition with COMPASS Aspect-Oriented Connectors
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    Chapter 15 Program Transformation Using HATS 1.84
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    Chapter 16 Using Java CSP Solvers in the Automated Analyses of Feature Models
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    Chapter 17 Co-transformations in Database Applications Evolution
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    Chapter 18 Modular Name Analysis for Java Using JastAdd
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    Chapter 19 Techniques for Lightweight Generator Refactoring
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    Chapter 20 E-CARES Project: Reengineering of Telecommunication Systems
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    Chapter 21 A Feature Composition Problem and a Solution Based on C++ Template Metaprogramming
Attention for Chapter 2: Generative and Transformational Techniques in Software Engineering
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Citations

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Readers on

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133 Mendeley
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6 CiteULike
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Chapter title
Generative and Transformational Techniques in Software Engineering
Chapter number 2
Book title
Generative and Transformational Techniques in Software Engineering
Published in
Lecture notes in computer science, May 2016
DOI 10.1007/11877028_2
Book ISBNs
978-3-54-045778-7, 978-3-54-046235-4
Authors

Jean Bézivin, Bézivin, Jean

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 3%
Spain 4 3%
United States 2 2%
Italy 1 <1%
Canada 1 <1%
Australia 1 <1%
China 1 <1%
Germany 1 <1%
Unknown 118 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 29%
Student > Master 28 21%
Researcher 17 13%
Student > Bachelor 11 8%
Student > Postgraduate 8 6%
Other 19 14%
Unknown 11 8%
Readers by discipline Count As %
Computer Science 96 72%
Engineering 20 15%
Physics and Astronomy 2 2%
Arts and Humanities 1 <1%
Economics, Econometrics and Finance 1 <1%
Other 0 0%
Unknown 13 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 May 2016.
All research outputs
#18,455,405
of 22,867,327 outputs
Outputs from Lecture notes in computer science
#6,012
of 8,127 outputs
Outputs of similar age
#218,658
of 298,725 outputs
Outputs of similar age from Lecture notes in computer science
#144
of 215 outputs
Altmetric has tracked 22,867,327 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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 298,725 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 215 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.