Efficient deterministic finite automata split-minimization derived from Brzozowski's algorithm

Minimization of deterministic finite automata is a classic problem in Computer Science which is still studied nowadays. In this paper, we relate the different split-minimization methods proposed to date, or to be proposed, and the algorithm due to Brzozowski which has been usually set aside in any classification of DFA minimization algorithms. In our work, we first propose a polynomial minimization method derived from a paper by Champarnaud et al. We also show how the consideration of some efficiency improvements on this algorithm lead to obtain an algorithm similar to Hopcroft s classic algorithm. The results obtained lead us to propose a characterization of the set of possible splitters.García Gómez, P.; López Rodríguez, D.; Vázquez-De-Parga Andrade, M. (2014). Efficient deterministic finite automata split-minimization derived from Brzozowski's algorithm. International Journal of Foundations of Computer Science. 25(6):679-696. doi:10.1142/S0129054114500282S679696256Vázquez de Parga, M., García, P., & López, D. (2013). A polynomial double reversal minimization algorithm for deterministic finite automata. Theoretical Computer Science, 487, 17-22. doi:10.1016/j.tcs.2013.03.005Courcelle, B., Niwinski, D., & Podelski, A. (1991). A geometrical view of the determinization and minimization of finite-state automata. Mathematical Systems Theory, 24(1), 117-146. doi:10.1007/bf02090394POLÁK, L. (2005). MINIMALIZATIONS OF NFA USING THE UNIVERSAL AUTOMATON. International Journal of Foundations of Computer Science, 16(05), 999-1010. doi:10.1142/s0129054105003431Gries, D. (1973). Describing an algorithm by Hopcroft. Acta Informatica, 2(2). doi:10.1007/bf00264025Blum, N. (1996). An O(n log n) implementation of the standard method for minimizing n-state finite automata. Information Processing Letters, 57(2), 65-69. doi:10.1016/0020-0190(95)00199-9Knuutila, T. (2001). Re-describing an algorithm by Hopcroft. Theoretical Computer Science, 250(1-2), 333-363. doi:10.1016/s0304-3975(99)00150-

A split-based incremental deterministic automata minimization algorithm

The final publication is available at Springer via http://dx.doi.org/10.1007/s00224-014-9588-y. La fecha de publicación corresponde a la versión First OnlineWe here study previous results due to Hopcroft and Almeida et al. to propose an incremental split-based deterministic automata minimization algorithm whose average running-time does not depend on the size of the alphabet. The experimentation carried out shows that our proposal outperforms the algorithms studied whenever the automata have more than a (quite small) number of states and symbols.García Gómez, P.; Vázquez-De-Parga Andrade, M.; Velasco, JA.; López Rodríguez, D. (2014). A split-based incremental deterministic automata minimization algorithm. Theory of Computing Systems. 1-18. doi:10.1007/s00224-014-9588-y118Hopcroft, J.E., Ullman, J.D.: Introduction to Automata Theory, Languages and Computation. Addison-Wesley Publishing Company (1979)Watson, B.W., Daciuk, J.: An efficient incremental DFA minimization algorithm. Nat. Lang. Eng. 9(1), 49–64 (2003)Almeida, M., Moreira, N., Reis, R.: Incremental DFA minimisation. In: Domaratzki, M., Salomaa, K. (eds.) CIAA, of Lecture Notes in Computer Science, vol. 6482, pp 39–48. Springer (2010)Hopcroft, J.E.: An n ⋅ log n $n\cdot \log n$ algorithm for minimizing states in a finite automaton. Technical report, Stanford, University, Stanford (1971)Moore, E.F.: Gedanken experiments on sequential machines. In: Shannon, C.E., Mc-Carthy, J. (eds.) Automata Studies. Princeton Universty Press, Princeton (1956)Berstel, J., Boasson, L., Carton, O., Fagnot, I.: Automata: from Mathematics to Applications, chapter Minimization of automata. European Mathematical Society. (arXiv: 1010.5318v3. ) To appear.David, J.: Average complexity of Moore’s and Hopcroft’s algorithms. Theor. Comput. Sci. 417, 50–65 (2012)Almeida, M., Moreira, N., Reis, R.: Aspects of enumeration and generation with a string automata representation. In: Leung, H., Pighizzini, G. (eds.) DCFS, pp 58–69. New Mexico State University, Las Cruces (2006)Gries, D.: Describing an algorithm by Hopcroft. Acta Informatica 2, 97–109 (1973)Aho, A., Hopcroft, J.E., Ullman, J.D.: The Design and Analysis of Computer Algorithms. Addison-Wesley Publishing Company (1974)Blum, N.: A O ( n log n ) $\mathcal {O}(n\log n)$ implementation of the standard method for minimizing n-state finite automata. Inf. Process. Lett. 57, 65–69 (1996)Knuutila, T.: Re-describing an algorithm by Hopcroft. Theor. Comput. Sci. 250, 333–363 (2001)Veanes, M.: Minimization of symbolic automata. Technical report, Microsoft Research, MSR-TR-2013-48 (2013)Lothaire, M.: Applied Combinatorics on Words chap. 1. Cambridge University Press, Cambridge (2005

Bisimulations over DLTS in O(m.log n)-time

The well known Hopcroft's algorithm to minimize deterministic complete automata runs in $O(kn\log n)$-time, where $k$ is the size of the alphabet and $n$ the number of states. The main part of this algorithm corresponds to the computation of a coarsest bisimulation over a finite Deterministic Labelled Transition System (DLTS). By applying techniques we have developed in the case of simulations, we design a new algorithm which computes the coarsest bisimulation over a finite DLTS in $O(m\log n)$-time and $O(k+m+n)$-space, with $m$ the number of transitions. The underlying DLTS does not need to be complete and thus: $m\leq kn$. This new algorithm is much simpler than the two others found in the literature.Comment: Submitted to DLT'1

Construction of minimal DFAs from biological motifs

Deterministic finite automata (DFAs) are constructed for various purposes in computational biology. Little attention, however, has been given to the efficient construction of minimal DFAs. In this article, we define simple non-deterministic finite automata (NFAs) and prove that the standard subset construction transforms NFAs of this type into minimal DFAs. Furthermore, we show how simple NFAs can be constructed from two types of patterns popular in bioinformatics, namely (sets of) generalized strings and (generalized) strings with a Hamming neighborhood