Buch, Englisch, 688 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 454 g
Reihe: Computational Analysis, Synthesis, and Design of Dynamic Systems
Buch, Englisch, 688 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 454 g
Reihe: Computational Analysis, Synthesis, and Design of Dynamic Systems
ISBN: 978-1-138-07645-7
Verlag: Taylor & Francis Ltd
What the experts have to say about Model-Based Testing for Embedded Systems:
"This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used and validated techniques, along with new ideas for solving hard problems.
"It is rare that a book can take recent research advances and present them in a form ready for practical use, but this book accomplishes that and more. I am anxious to recommend this in my consulting and to teach a new class to my students."
—Dr. Jeff Offutt, professor of software engineering, George Mason University, Fairfax, Virginia, USA
"This handbook is the best resource I am aware of on the automated testing of embedded systems. It is thorough, comprehensive, and authoritative. It covers all important technical and scientific aspects but also provides highly interesting insights into the state of practice of model-based testing for embedded systems."
—Dr. Lionel C. Briand, IEEE Fellow, Simula Research Laboratory, Lysaker, Norway, and professor at the University of Oslo, Norway
"As model-based testing is entering the mainstream, such a comprehensive and intelligible book is a must-read for anyone looking for more information about improved testing methods for embedded systems. Illustrated with numerous aspects of these techniques from many contributors, it gives a clear picture of what the state of the art is today."
—Dr. Bruno Legeard, CTO of Smartesting, professor of Software Engineering at the University of Franche-Comté, Besançon, France, and co-author of Practical Model-Based Testing
Zielgruppe
Engineers, analysts, and computer scientists involved in the analysis and development of embedded systems, software, and their quality assurance.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Part I: Introduction
A Taxonomy of Model-Based Testing for Embedded Systems from Multiple Industry Domains. Behavioral System Models versus Models of Testing Strategies in Functional Test Generation. Test Framework Architectures for Model-Based Embedded System Testing.
Part II: Automatic Test Generation
Automatic Model-Based Test Generation from UML State Machines. Automated Statistical Testing for Embedded Systems. How to Design Extended Finite State Machine Test Models in Java. Automatic Testing of LUSTRE/SCADE Programs. Test Generation Using Symbolic Animation of Models.
Part III: Integration and Multi-level Testing
Model-Based Integration Testing with Communication Sequence Graphs. A Model-Based View onto Testing: Criteria for the Derivation of Entry Tests for Integration Testing. Multilevel Testing for Embedded Systems. Model-Based X-in-the-Loop Testing.
Part IV: Specific Approaches
A Survey of Model-Based Software Product Lines Testing. Model-Based Testing of Hybrid Systems. Reactive Testing of Nondeterministic Systems by Test Purpose-Directed Tester. Model-Based Passive Testing of Safety-Critical Components.
Part V: Testing in Industry
Applying Model-Based Testing in the Telecommunication Domain. Model-Based GUI Testing of Smartphone Applications: Case S60™ and Linux®. Model-Based Testing in Embedded Automotive Systems.
Part VI: Testing at the Lower Levels of Development
Testing-Based Translation Validation of Generated Code. Model-Based Testing of Analog Embedded Systems Components. Dynamic Verification of SystemC Transactional Models.