Formal Methods for Protocol Testing: A Detailed Study
IEEE Transactions on Software Engineering
Bisimulation through probabilistic testing
Information and Computation
Distinguishing tests for nondeterministic and probabilistic machines
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Testing deterministic implementations from nondeterministic FSM specifications
Selected proceedings of the IFIP TC6 9th international workshop on Testing of communicating systems
Automatic verification of real-time systems with discrete probability distributions
Theoretical Computer Science
IEEE Transactions on Software Engineering
Probabilistic simulations for probabilistic processes
Nordic Journal of Computing
An Efficient Non-repudiation Protocol
CSFW '97 Proceedings of the 10th IEEE workshop on Computer Security Foundations
Testing from a Nondeterministic Finite State Machine Using Adaptive State Counting
IEEE Transactions on Computers
Specification, testing and implementation relations for symbolic-probabilistic systems
Theoretical Computer Science
Mutation Testing from Probabilistic Finite State Machines
TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
Testing Software Design Modeled by Finite-State Machines
IEEE Transactions on Software Engineering
A testing scenario for probabilistic processes
Journal of the ACM (JACM)
Formal testing from timed finite state machines
Computer Networks: The International Journal of Computer and Telecommunications Networking
Algorithms for Modeling a Class of Single Timing Faults in Communication Protocols
IEEE Transactions on Computers
Test selection for a nondeterministic FSM
Computer Communications
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In this paper, we propose a method to test a probabilistic FSM. The testing process consists of two parts. First, we check if there are any output faults or transfer faults in transitions. In order to identify a state of a PFSM, the characterization set is extended such that states are identified not only by observing output sequences but also by comparing probabilities. Second, we test whether the transition probabilities are correctly implemented. Interval estimation is used to assert the correctness of transition probabilities where a test verdict is assigned with a given confidence level. From a given confidence level and confidence interval length, a method is presented to determine the test sequence repetition numbers for testing probabilities. Fault coverage evaluation is carried out based on extended fault types where probabilities are changed. As an application, we apply the proposed method to a probabilistic non-repudiation protocol.