Theoretical Computer Science
Testing real-time constraints in a process algebraic setting
Proceedings of the 17th international conference on Software engineering
Real-Time UML: Developing Efficient Objects for Embedded Systems
Real-Time UML: Developing Efficient Objects for Embedded Systems
Art of Software Testing
Theory of Modeling and Simulation
Theory of Modeling and Simulation
IEEE Transactions on Software Engineering
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Practical Model-Based Testing: A Tools Approach
Practical Model-Based Testing: A Tools Approach
Journal of Systems and Software
Automated generation of test suites from formal specifications of real-time reactive systems
Journal of Systems and Software
A scalable method for testing real-time systems
Software Quality Control
Functional Search-based Testing from State Machines
ICST '08 Proceedings of the 2008 International Conference on Software Testing, Verification, and Validation
Conformance testing for real-time systems
Formal Methods in System Design
Adaptive Random Testing: The ART of test case diversity
Journal of Systems and Software
Integrating Model-Based Testing with Evolutionary Functional Testing
ICSTW '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification, and Validation Workshops
It Does Matter How You Normalise the Branch Distance in Search Based Software Testing
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
Longer is Better: On the Role of Test Sequence Length in Software Testing
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
Formal analysis of the effectiveness and predictability of random testing
Proceedings of the 19th international symposium on Software testing and analysis
MODELS'10 Proceedings of the 13th international conference on Model driven engineering languages and systems: Part I
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Proceedings of the 33rd International Conference on Software Engineering
Adaptive random testing: an illusion of effectiveness?
Proceedings of the 2011 International Symposium on Software Testing and Analysis
On parameter tuning in search based software engineering
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
A real-world benchmark model for testing concurrent real-time systems in the automotive domain
ICTSS'11 Proceedings of the 23rd IFIP WG 6.1 international conference on Testing software and systems
Proceedings of the 2012 International Symposium on Software Testing and Analysis
Sound empirical evidence in software testing
Proceedings of the 34th International Conference on Software Engineering
Experiences of applying UML/MARTE on three industrial projects
MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
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Testing real-time embedded systems (RTES) is in many ways challenging. Thousands of test cases can be potentially executed on an industrial RTES. Given the magnitude of testing at the system level, only a fully automated approach can really scale up to test industrial RTES. In this paper we take a black-box approach and model the RTES environment using the UML/- MARTE international standard. Our main motivation is to provide a more practical approach to the model-based testing of RTES by allowing system testers, who are often not familiar with the system design but know the application domain well-enough, to model the environment to enable test automation. Environment models can support the automation of three tasks: the code generation of an environment simulator, the selection of test cases, and the evaluation of their expected results (oracles). In this paper, we focus on the second task (test case selection) and investigate three test automation strategies using inputs from UML/MARTE environment models: Random Testing (baseline), Adaptive Random Testing, and Search-Based Testing (using Genetic Algorithms). Based on one industrial case study and three artificial systems, we show how, in general, no technique is better than the others. Which test selection technique to use is determined by the failure rate (testing stage) and the execution time of test cases. Finally, we propose a practical process to combine the use of all three test strategies.