Model Driven Engineering for Distributed Real-Time Embedded Systems: Advances, Standards, Applications and Perspectives

250 Pages·2010·8.312 MB·English

by  Jean-Philippe Babau, Mireille Blay-Fornarino, Joel Champeau, Sylvain Robert, Antonino Sabetta

Model-Driven Engineering
for Distributed Real-Time Systems
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Model-Driven Engineering
for Distributed
Real-Time Systems
MARTE Modeling, Model Transformations
and their Usages

Edited by
Jean-Philippe Babau
Mireille Blay-Fornarino
Joël Champeau
Sylvain Robert
Antonio Sabetta

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First published 2010 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

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The rights of Jean-Philippe Babau, Mireille Blay-Fornarino, Joël Champeau, Sylvain Robert and Antonio
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Library of Congress Cataloging-in-Publication Data

Model-driven engineering for distributed real-time systems : MARTE modeling, model transformations,
and their usages / edited by Jean-Philippe Babau ... [et al.].
p. cm.
Includes bibliographical references and index.
ISBN 978-1-84821-115-5
1. Model-driven software architecture. 2. Electronic data processing--Distributed processing. 3. Real-
time data processing. 4. UML (Computer science). I. Babau, Jean-Philippe.

QA76.76.D47M622 2010
005.2'732--dc22
2010027955

British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-84821-115-5

Printed and bound in Great Britain by CPI Antony Rowe, Chippenham and Eastbourne.

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Table of Contents
Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . xi
Chapter 1. Model Transformation: A Survey
of the State of the Art . . . . . . . . . . . . . . . . . . . . . 1
Tom MENS
1.1. Model-driven engineering . . . . . . . . . . . . . . . . . 1
1.2. Model transformation . . . . . . . . . . . . . . . . . . . 2
1.2.1. Definitions . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.2. Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3. Model transformation languages . . . . . . . . . . . . 5
1.4. Model transformation activities . . . . . . . . . . . . 8
1.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . 14
1.7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Chapter 2. Model-Based Code Generation . . . . . 21
Chris RAISTRICK
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2. The model-driven architecture (MDA) process . . 22
2.3. The automated approach to code generation . . . . 23
2.4. Domain modeling . . . . . . . . . . . . . . . . . . . . . . 25
2.5. The executable UML (xUML) formalism . . . . . . 29
2.6. System generation . . . . . . . . . . . . . . . . . . . . . . 31
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2.7. Executable UML to code mappings . . . . . . . . . . 34
2.8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.9. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Chapter 3. Testing Model Transformations:
A Case for Test Generation from Input Domain
Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Benoit BAUDRY
3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2. Challenges for testing systems with large input
domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.2.1. Large set of input data . . . . . . . . . . . . . . . . 46
3.2.2. Configurable systems . . . . . . . . . . . . . . . . . 48
3.2.3. Grammarware and model transformations . . 48
3.2.4. Testing challenges . . . . . . . . . . . . . . . . . . . 52
3.3. Selecting test data in large domains . . . . . . . . . 52
3.3.1. Category partition . . . . . . . . . . . . . . . . . . . 52
3.3.2. Combinatorial interaction testing . . . . . . . . 55
3.4. Metamodel-based test input generation . . . . . . . 58
3.4.1. Metamodel coverage criteria . . . . . . . . . . . . 59
3.4.2. Model and object fragments for test
adequacy criteria . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.3. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.4.4. Automatic synthesis of test models . . . . . . . 65
3.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . 68
3.7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Chapter 4. Symbolic Execution-Based
Techniques for Conformance Testing . . . . . . . . 73
Christophe GASTON, Pascale LE GALL, Nicolas RAPIN and Assia
TOUIL
4.1. Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.1.1. Conformance testing: an introduction . . . . . 73
4.1.2. Conformance relation . . . . . . . . . . . . . . . . . 74
4.1.3. An overview of the approach . . . . . . . . . . . . 78
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4.2. Input output symbolic transition systems . . . . . 79
4.2.1. Data types . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.2.2. Input/output symbolic transition systems . . . 80
4.2.3. Semantics . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.3. Symbolic execution . . . . . . . . . . . . . . . . . . . . . 84
4.4. Conformance testing for IOSTS . . . . . . . . . . . . 87
4.4.1. Test purposes . . . . . . . . . . . . . . . . . . . . . . . 88
4.4.2. Preliminary definitions and informal
description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.4.3. Inference rules . . . . . . . . . . . . . . . . . . . . . . 94
4.5. Concluding remarks . . . . . . . . . . . . . . . . . . . . 96
4.5.1. Choosing test purposes . . . . . . . . . . . . . . . . 96
4.5.2. Implementation issues . . . . . . . . . . . . . . . . 101
4.6. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Chapter 5. Using MARTE and SysML for
Modeling Real-Time Embedded Systems . . . . . . 105
Huascar ESPINOZA, Daniela CANCILA,
Sébastien GÉRARD and Bran SELIC
5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 105
5.2. Background . . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.2.1. UML profiling capabilities . . . . . . . . . . . . . . 108
5.2.2. SysML and MARTE modeling capabilities . . 111
5.3. Scenarios of combined usage . . . . . . . . . . . . . . . 113
5.3.1. Defining architecture frameworks . . . . . . . . 114
5.3.2. Requirements engineering . . . . . . . . . . . . . . 115
5.3.3. System-level design integration . . . . . . . . . . 117
5.3.4. Engineering/quantitative analysis . . . . . . . . 120
5.4. Combination Strategies . . . . . . . . . . . . . . . . . . 125
5.4.1. Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.4.2. Strategies . . . . . . . . . . . . . . . . . . . . . . . . . 128
5.5. Related work. . . . . . . . . . . . . . . . . . . . . . . . . . 130
5.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
5.7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . 134
5.8. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 134
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Chapter 6. Software Model-based Performance
Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Dorina C. PETRIU
6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.2. Performance models . . . . . . . . . . . . . . . . . . . . 142
6.2.1. Queuing network models . . . . . . . . . . . . . . 144
6.2.2. Layered queuing network model . . . . . . . . . 146
6.3. Software model with performance annotations . . 148
6.3.1. Performance domain model . . . . . . . . . . . . . 148
6.3.2. Source model example . . . . . . . . . . . . . . . . 152
6.4. Mapping from software to performance model . . 155
6.5. Using a pivot language: Core Scenario
Model (CSM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
6.6. Case study performance model . . . . . . . . . . . . . 160
6.7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 162
6.8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . 163
6.9. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Chapter 7. Model Integration for Formal
Qualification of Timing-Aware Software Data
Acquisition Components . . . . . . . . . . . . . . . . . . 167
Jean-Philippe BABAU, Philippe DHAUSSY and
Pierre-Yves PILLAIN
7.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 167
7.2. System modeling . . . . . . . . . . . . . . . . . . . . . . . 170
7.2.1. Acquisition system modeling . . . . . . . . . . . . 170
7.2.2. Case study . . . . . . . . . . . . . . . . . . . . . . . . 172
7.2.3. Formal modeling techniques . . . . . . . . . . . . 174
7.3. Variation points modeling . . . . . . . . . . . . . . . . 182
7.3.1. Variation points definition . . . . . . . . . . . . . 184
7.3.2. CDL implementation . . . . . . . . . . . . . . . . . 187
7.4. Experiments and results . . . . . . . . . . . . . . . . . 189
7.4.1. Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
7.4.2. Experimentations . . . . . . . . . . . . . . . . . . . 191
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7.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
7.6. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Chapter 8. SoC/SoPC Development using MDD
and MARTE Profile . . . . . . . . . . . . . . . . . . . . . . 201
Denis AULAGNIER, Ali KOUDRI, Stéphane LECOMTE, Philippe
SOULARD, Joël CHAMPEAU, Jorgiano VIDAL,
Gilles PERROUIN and Pierre LERAY
8.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 201
8.2. Related works . . . . . . . . . . . . . . . . . . . . . . . . . 203
8.3. MOPCOM process and models . . . . . . . . . . . . . 206
8.4. Application . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
8.5. System analysis . . . . . . . . . . . . . . . . . . . . . . . 211
8.5.1. Requirement analysis . . . . . . . . . . . . . . . . . 211
8.5.2. Functional analysis . . . . . . . . . . . . . . . . . . 212
8.5.3. Action language . . . . . . . . . . . . . . . . . . . . . 213
8.6. Abstract modeling level . . . . . . . . . . . . . . . . . . 214
8.7. Execution modeling level . . . . . . . . . . . . . . . . . 216
8.7.1. The platform independent model/application
model in EML . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
8.7.2. The platform model in EML . . . . . . . . . . . . 217
8.7.3. The platform specific model/allocation model
in EML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
8.7.4. Analysis model . . . . . . . . . . . . . . . . . . . . . . 219
8.8. Detailed modeling level . . . . . . . . . . . . . . . . . . 220
8.8.1. Platform model . . . . . . . . . . . . . . . . . . . . . 221
8.8.2. Allocation model . . . . . . . . . . . . . . . . . . . . . 222
8.9. Tooling Support . . . . . . . . . . . . . . . . . . . . . . . 223
8.9.1. Process validation through metamodeling
with Kermeta . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
8.9.2. Model transformation and generation with
MDWorkbench platform . . . . . . . . . . . . . . . . . . . 224
8.10. HDL Code Generation . . . . . . . . . . . . . . . . . . 225
8.10.1. VHDL code generation . . . . . . . . . . . . . . . 226
8.10.2. Rhapsody integration . . . . . . . . . . . . . . . . 227
8.11. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 228
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8.12. Acknowledgements . . . . . . . . . . . . . . . . . . . . 229
8.13. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . 229
List of Authors . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
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