Efficient parallel derivation of short distinguishing sequences for nondeterministic finite state machines using MapReduce

Distinguishing sequences are widely used in finite state machine-based conformance testing to solve the state identification problem. In this paper, we address the scalability issue encountered while deriving distinguishing sequences from complete observable nondeterministic finite state machines by introducing a massively parallel MapReduce version of the well-known Exact Algorithm. To the best of our knowledge, this is the first study to tackle this task using the MapReduce approach. First, we give a concise overview of the well-known Exact Algorithm for deriving distinguishing sequences from nondeterministic finite state machines. Second, we propose a parallel algorithm for this problem using the MapReduce approach and analyze its communication cost using Afrati et al. model. Furthermore, we conduct a variety of intensive and comparative experiments on a wide range of finite state machine classes to demonstrate that our proposed solution is efficient and scalable.

Research on the Properties of Lattice-Valued Finite State Machines in Computer Technology

In this paper, we discuss some algebraic properties of Lattice valued finite state machine and prove that if there are homomorphic mapping satisfying certain conditions between two Lattice valued finite state machines, the first one is strongly connected (cycle), then then the second one is the same. And if the homomorphism is strongly homomorphic, one of the Lattice valued finite state machines is complete if and only if another Lattice valued finite state machine is complete. Discuss the completeness, strong connectivity, circulation and exchange capacity between the product of a Lattice valued finite state machine and the original Lattice valued finite state machine and get some results.