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A highly configurable test system for evolutionary black-box testing of embedded systems
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents
Montreal, Québec, Canada
SESSION: Track 13: real world application table of contents
Pages 1545-1552  
Year of Publication: 2009
ISBN:978-1-60558-325-9
Authors
Peter M. Kruse  Berner & Mattner Systemtechnik GmbH, Berlin, Germany
Joachim Wegener  Berner & Mattner Systemtechnik GmbH, Berlin, Germany
Stefan Wappler  Berner & Mattner Systemtechnik GmbH, Berlin, Germany
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

During the development of electronic control units (ECU) in domains like the automotive industry, tests are performed on various test platforms, such as model-in-the-loop, software-in-the-loop, processor-in-the-loop, and hardware-in-the-loop platforms in order to find faults in early development stages. Test cases must be specified to verify the properties demanded of the system on these test platforms. This is an expensive and non-trivial task. Evolutionary black-box testing, a recent approach to automating the creation of interesting test cases, can solve this task completely automatically.

This paper describes our evolutionary test system and how to apply it to the test of functional and non-functional properties of embedded systems. Our system supports the aforementioned test platforms and allows for the reuse of the generated test cases across them. In a case study with an antilock braking system, we demonstrate the operation of the system.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Berner&Mattner Systemtechnik GmbH MESSINA. http://berner-mattner.com/automotive-messina.php
 
2
Berner&Mattner Systemtechnik GmbH modularHiL http://berner-mattner.com/automotive-modulhil.php
 
3
Da Costa, L.; Schoenauer, M.: GUIDE, a Graphical User Interface for Evolutionary Algorithms. GECCO Workshop on Open-Source Software for Applied Genetic and Evolutionary Computation (SoftGEC), 2007.
 
4
Dimitar, M.; Dimitrov, I. M.; Spasov, I.: Evotest -- Framework for customizable implementation of Evolutionary Testing. International Workshop on Software and Services, October 2008, Sofia, Bulgaria.
 
5
EvoTest http://www.evotest.eu/
 
6
GUIDE. http://guide.gforge.inria.fr/
 
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Jones, B.F., Eyres, D.E. and Sthamer, H.-H.: A Strategy for using Genetic Algorithms to Automate Branch and Fault-based Testing. The Computer Journal, vol. 41, no. 2, pp. 98--107, 1998.
 
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9
Sthamer, H.-H.: The Automatic Generation of Software Test Data Using Genetic Algorithms. PhD Thesis, University of Glamorgan, Pontyprid, Wales, Great Britain, 1996.
 
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Wegener, J., Baresel, A., Sthamer H.: Evolutionary Test Environment for Automatic Structural Testing. Information and Software Technology, Special Issue devoted to the Application of Metaheuristic Algorithms to Problems in Software Engineering, vol. 43, pp. 841--854, 2001.
 
13
Wegener, J.: Evolutionärer Test des Zeitverhaltens von Realzeit-Sytemen (Evolutionary Testing of the Temporal Behaviour of Real-Time Systems). Shaker Verlag, 2001.
 
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Windisch, A.: Search-Based Testing of Complex Simulink Models containing Stateflow Diagrams. Proceedings of the 1st International Workshop on Search-Based Software Testing, Lillehammer, Norway, 2008.

Collaborative Colleagues:
Peter M. Kruse: colleagues
Joachim Wegener: colleagues
Stefan Wappler: colleagues