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SDL 2013: Model-Driven Dependability Engineering

Overview of attention for book
Cover of 'SDL 2013: Model-Driven Dependability Engineering'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Data Flow Testing in TTCN-3 with a Relational Database Schema
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    Chapter 2 Property Verification with MSC
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    Chapter 3 Towards the Generation of AMF Configurations from Use Case Maps Based Availability Requirements
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    Chapter 4 Modeling Early Availability Requirements Using Aspect-Oriented Use Case Maps
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    Chapter 5 Model-Driven Engineering for Trusted Embedded Systems Based on Security and Dependability Patterns
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    Chapter 6 Static Analysis Techniques to Verify Mutual Exclusion Situations within SysML Models
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    Chapter 7 Significantly Increasing the Usability of Model Analysis Tools through Visual Feedback
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    Chapter 8 Modeling Component Erroneous Behavior and Error Propagation for Dependability Analysis
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    Chapter 9 An IMS DSL Developed at Ericsson
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    Chapter 10 Efficient Development of Domain-Specific Simulation Modelling Languages and Tools
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    Chapter 11 FTG+PM: An Integrated Framework for Investigating Model Transformation Chains
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    Chapter 12 Traceability Links in Model Transformations between Software and Performance Models
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    Chapter 13 Refactorings in Language Development with Asymmetric Bidirectional Model Transformations
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    Chapter 14 SDL Real-Time Tasks – Concept, Implementation, and Evaluation
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    Chapter 15 Definition of Virtual Reality Simulation Models Using Specification and Description Language Diagrams
  17. Altmetric Badge
    Chapter 16 Integration of SDL Models into a SystemC Project for Network Simulation
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

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2 X users
wikipedia
7 Wikipedia pages

Citations

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4 Dimensions

Readers on

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6 Mendeley
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Title
SDL 2013: Model-Driven Dependability Engineering
Published by
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-38911-5
ISBNs
978-3-64-238910-8, 978-3-64-238911-5
Authors

Pascal Potvin, Mario Bonja, Gordon Bailey, Pierre Busnel

Editors

Khendek, Ferhat, Toeroe, Maria, Gherbi, Abdelouahed, Reed, Rick

X Demographics

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 12 September 2022.
All research outputs
#6,312,689
of 23,317,888 outputs
Outputs from Lecture notes in computer science
#2,028
of 8,159 outputs
Outputs of similar age
#66,398
of 283,761 outputs
Outputs of similar age from Lecture notes in computer science
#80
of 316 outputs
Altmetric has tracked 23,317,888 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 8,159 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 gotten more attention than average, scoring higher than 74% 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 283,761 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 76% of its contemporaries.
We're also able to compare this research output to 316 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.