Abstract We consider the notion of a constant length queue automaton—i.e., a traditional queue automaton with a built-in constant limit on the length of its queue—as a formalism for representing regular languages. We show that the descriptional power of constant length queue automata greatly outperforms that of traditional finite state automata, of constant height pushdown automata, and of straight line programs for regular expressions, by providing optimal exponential and double-exponential size gaps. Moreover, we prove that constant height pushdown automata can be simulated by constant length queue automata paying only by a linear size increase, and that removing nondeterminism in constant length queue automata requires an optimal exponential size blow-up, against the optimal double-exponential cost for determinizing constant height pushdown automata. Finally, we investigate the size cost of implementing Boolean language operations on deterministic and nondeterministic constant length queue automata.

We investigate the state complexity of the cut and iterated cut operation for deterministic finite automata (DFAs), answering an open question stated in [M. BERGLUND, et al.: Cuts in regular expressions. In Proc. DLT, LNCS 7907, 2011]. These operations can be seen as an alternative to ordinary conc atenation and Kleene star modelling leftmost maximal string matching. We show that the cut operation has a matching upper and lower bound of n states, if m = 1, and (n–1)·m+n states, otherwise, on DFAs accepting the cut of two individual languages that are accepted by n- and m-state DFAs, respectively. In the unary case we obtain max(2n–1,m+n–2) states as a tight bound—notice that for m ≤ n the bound for unary DFAs only depends on the former automaton and not on the latter. For accepting the iterated cut of a language accepted by an n-state DFA we find a matching bound of 1+(n+1) · F(1,n+2,–n+2;n+1 | –1) states on DFAs, if n ≥ 4 and where F refers to the generalized hypergeometric function. This bound is in the order of magnitude Θ((n – 1)!). Finally, the bound drops to 2n – 1 for unary DFAs accepting the iterated cut of an n-state DFA, if n ≥ 3, and thus is similar to the bound for the cut operation on unary DFAs.

We consider the computational complexity of problems related to partial word automata. Roughly speaking, a partial word is a word in which some positions are unspecified and a partial word automaton is a finite automaton that accepts a partial word language—here the unspecified positions in the wor d are represented by a “hole” symbol ⋄. A partial word language L′ can be transformed into an ordinary language L by using a ⋄-substitution. In particular, we investigate the complexity of the compression or minimization problem for partial word automata, which is known to be NP-hard. We improve on the previously known complexity on this problem, by showing PSPACE-completeness. In fact, it turns out that almost all problems related to partial word automata, such as, e.g., equivalence and universality, are already PSPACE-complete. Moreover, we also study these problems under the further restriction that the involved automata accept only finite languages. In this case, the complexities of the studied problems drop from PSPACE-completeness down to coNP-hardness and containment in ∑2P depending on the problem investigated.

We show how to minimize biautomata with adaptations of classical minimization algorithms for ordinary deterministic finite automata and moreover by a Brzozowski-like minimization algorithm by applying reversal and power-set construction twice to the