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Software Engineering for Resilient Systems

Overview of attention for book
Cover of 'Software Engineering for Resilient Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Preliminary Interdependency Analysis (PIA): Method and Tool Support
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    Chapter 2 Use Case Scenarios as Verification Conditions: Event-B/Flow Approach
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    Chapter 3 Quantitative Verification of System Safety in Event-B
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    Chapter 4 Experience-Based Model Refinement
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    Chapter 5 Architecting Resilient Computing Systems: Overall Approach and Open Issues
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    Chapter 6 Supporting Architectural Design Decisions Evolution through Model Driven Engineering
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    Chapter 7 On Enabling Dependability Assurance in Heterogeneous Networks through Automated Model-Based Analysis
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    Chapter 8 Supporting Cross-Language Exception Handling When Extending Applications with Embedded Languages
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    Chapter 9 Guaranteeing Correct Evolution of Software Product Lines: Setting Up the Problem
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    Chapter 10 Idealized Fault-Tolerant Components in Requirements Engineering
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    Chapter 11 Predictability and Evolution in Resilient Systems
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    Chapter 12 Self-organising Pervasive Ecosystems: A Crowd Evacuation Example
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    Chapter 13 Towards a Model-Driven Infrastructure for Runtime Monitoring
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    Chapter 14 Using Diversity in Cloud-Based Deployment Environment to Avoid Intrusions
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    Chapter 15 ‘Known Secure Sensor Measurements’ for Critical Infrastructure Systems: Detecting Falsification of System State
Overall attention for this book and its chapters
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Mentioned by

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1 Wikipedia page

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mendeley
61 Mendeley
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Title
Software Engineering for Resilient Systems
Published by
Springer Berlin Heidelberg, September 2011
DOI 10.1007/978-3-642-24124-6
ISBNs
978-3-64-224123-9, 978-3-64-224124-6
Editors

Troubitsyna, Elena A.

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 %
Italy 1 2%
Hungary 1 2%
Unknown 59 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 18 30%
Student > Ph. D. Student 13 21%
Student > Bachelor 9 15%
Researcher 7 11%
Unspecified 5 8%
Other 9 15%
Readers by discipline Count As %
Computer Science 33 54%
Engineering 12 20%
Unspecified 6 10%
Business, Management and Accounting 3 5%
Arts and Humanities 1 2%
Other 6 10%