Theoretical Computer Science
Interval arithmetic: From principles to implementation
Journal of the ACM (JACM)
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Discrete-Time Control for Rectangular Hybrid Automata
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Coverage Criteria for Logical Expressions
ISSRE '03 Proceedings of the 14th International Symposium on Software Reliability Engineering
A Generic Method for Statistical Testing
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
The HybridUML profile for UML 2.0
International Journal on Software Tools for Technology Transfer (STTT) - Special Section on Specification and Validation of Models of Real Time and Embedded Systems with UML
Specification of Conditions for Error Diagnostics
Electronic Notes in Theoretical Computer Science (ENTCS)
Symbolic and Abstract Interpretation for C/C++ Programs
Electronic Notes in Theoretical Computer Science (ENTCS)
A Unified Approach to Abstract Interpretation, Formal Verification and Testing of C/C++ Modules
Proceedings of the 5th international colloquium on Theoretical Aspects of Computing
A domain-oriented, model-based approach for construction and verification of railway control systems
Formal methods and hybrid real-time systems
Test harness and script design principles for automated testing of non-GUI or web based applications
Proceedings of the First International Workshop on End-to-End Test Script Engineering
Integrated and automated abstract interpretation, verification and testing of c/c++ modules
Concurrency, Compositionality, and Correctness
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This article presents novel results on automated test generation for hybrid control systems, which involves the generation of both discrete and real-valued, potentially time-continuous, input data to the system under test. Our generation techniques are allocated in two layers: The upper layer contains a symbolic test case generator constructing test cases as paths through an abstracted representation model of the system under test. Different test strategies designed to pursue various quality objectives lead to different selections of symbolic test cases. Symbolic test cases are transformed into feasible, i. e., executable, test cases by constructing concrete sequences of input data, allowing the execution of the pre-planned transition sequence. The input data construction is performed by the lower layer consisting of a constraint solver which applies interval analysis techniques to identify the domains from where to pick the appropriate test data. This process is made efficient by combining subpaving with forward-backward interval constraint propagation. On both layers learning algorithms are applied in order to avoid the spending of computation time on paths and sub-constraints, respectively, which are already known not to contribute to the solution.