Distinguishing tests for nondeterministic and probabilistic machines
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FORTE XII / PSTV XIX '99 Proceedings of the IFIP TC6 WG6.1 Joint International Conference on Formal Description Techniques for Distributed Systems and Communication Protocols (FORTE XII) and Protocol Specification, Testing and Verification (PSTV XIX)
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CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
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QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
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Concrete model checking with abstract matching and refinement
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Using anti-ant-like agents to generate test threads from the UML diagrams
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Learning the Difference between Partially Observable Dynamical Systems
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
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Coverage rewarded: Test input generation via adaptation-based programming
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
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ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: technologies for mastering change - Volume Part I
Testing probabilistic equivalence through Reinforcement Learning
Information and Computation
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Online testing is a practical technique where test derivation and test execution are combined into a single algorithm. In this paper we describe a new online testing algorithm that optimizes the choice of test actions using Reinforcement Learning (RL) techniques. This provides an advantage in covering system behaviors in less time than with a purely random choice of test actions. Online testing with conformance checking is modeled as a 1$\frac{1}{2}$-player game, or Markov Decision Process (MDP), between the tester as one player and the implementation under test (IUT) as the opponent. Our approach has been implemented in C#, and benchmark results are presented in the paper. The specifications that generate the tests are written as model programs in any .NET language such as C# or VB.