Reset sequences for monotonic automata
SIAM Journal on Computing
8.2 On Synchronizing Sequences and Test Sequence Partitioning
VTS '98 Proceedings of the 16th IEEE VLSI Test Symposium
ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
Beyond the C++ Standard Library
Beyond the C++ Standard Library
An algorithmic approach to the automated design of parts orienters
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Synchronizing monotonic automata
DLT'03 Proceedings of the 7th international conference on Developments in language theory
The complexity of finding reset words in finite automata
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
Experimental study of the shortest reset word of random automat
CIAA'11 Proceedings of the 16th international conference on Implementation and application of automata
An efficient algorithm finds noticeable trends and examples concerning the Černy conjecture
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Exact calculation of synchronizing sequences based on binary decision diagrams
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Generating small automata and the Černý conjecture
CIAA'13 Proceedings of the 18th international conference on Implementation and Application of Automata
| Hi-index | 12.05 |
The notion of a synchronizing sequence plays an important role in the model-based testing of reactive systems, such as sequential circuits or communication protocols. The main problem in this approach is to find the shortest possible sequence which synchronizes the automaton being a model of the system under test. This can be done with a synchronizing algorithm. In this paper we analyze the synchronizing algorithms described in the literature, both exact (with exponential runtime) and greedy (polynomial). We investigate the implementation of the exact algorithm and show how this implementation can be optimized by use of some efficient data structures. We also propose a new greedy algorithm, which relies on some new heuristics. We compare our algorithms with the existing ones, with respect to both runtime and quality aspect.