Algebraic theory of processes
A timed model for communicating sequential processes
Theoretical Computer Science - Thirteenth International Colloquim on Automata, Languages and Programming, Renne
Bisimulation through probabilistic testing
Information and Computation
Reactive, generative, and stratified models of probabilistic processes
Information and Computation
Testing preorders for probabilistic processes
Information and Computation
A note on reliable full-duplex transmission over half-duplex links
Communications of the ACM
Art of Software Testing
Process Algebra with Timing
Discrete time generative-reactive probabilistic processes with different advancing speeds
Theoretical Computer Science
Testing Probabilistic and Nondeterministic Processes
Proceedings of the IFIP TC6/WG6.1 Twelth International Symposium on Protocol Specification, Testing and Verification XII
Testing Semantics for Probabilistic LOTOS
Proceedings of the IFIP TC6 Eighth International Conference on Formal Description Techniques VIII
Testing Concurrent Systems: A Formal Approach
CONCUR '99 Proceedings of the 10th International Conference on Concurrency Theory
Testing Equivalences and Fully Abstract Models for Probabilistic Processes
CONCUR '90 Proceedings of the Theories of Concurrency: Unification and Extension
Testing Probabilistic Automata
CONCUR '96 Proceedings of the 7th International Conference on Concurrency Theory
An Overview and Synthesis on Timed Process Algebras
CAV '91 Proceedings of the 3rd International Workshop on Computer Aided Verification
A testing scenario for probabilistic automata
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Specification, testing and implementation relations for symbolic-probabilistic systems
Theoretical Computer Science
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In this paper we consider the testing of systems where probabilistic information is not given by means of fixed values but as sets of probabilities. We will use an extension of finite state machine where choices among transitions labeled by the same input are probabilistically resolved. We will introduce our notion of test and we will define how tests are applied to the implementation under test (IUT). We will also present an implementation relation to assess the conformance, up to a level of confidence, of an implementation to a specification. In order to define this relation we will take finite samples of executions of the implementation and compare them with the probabilistic constraints imposed by the specification. Finally, we will give an algorithm for deriving sound and complete test suites with respect to this implementation relation.