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  • 1. Abdulla, Parosh Aziz
    et al.
    Högberg, Johanna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kaati, Lisa
    Bisimulation minimization of tree automata2007In: International Journal of Foundations of Computer Science, ISSN 0129-0541, Vol. 18, no 4, p. 699-713Article in journal (Refereed)
    Abstract [en]

    We extend an algorithm by Paige and Tarjan that solves the coarsest stable refinement problem to the domain of trees. The algorithm is used to minimize nondeterministic tree automata (NTA) with respect to bisimulation. We show that our algorithm has an overall complexity of $O(\hat{r} m \log n)$, where $\hat{r}$ is the maximum rank of any symbol in the input alphabet, m is the total size of the transition table, and n is the number of states.

  • 2.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Johanna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kutrib, Martin
    Deterministic Stack Transducers2017In: International Journal of Foundations of Computer Science, ISSN 0129-0541, Vol. 28, no 5, p. 583-601Article in journal (Refereed)
    Abstract [en]

    We introduce and investigate stack transducers, which are one-way stack automata with an output tape. A one-way stack automaton is a classical pushdown automaton with the additional ability to move the stack head inside the stack without altering the contents. For stack transducers, we distinguish between a digging and a non-digging mode. In digging mode, the stack transducer can write on the output tape when its stack head is inside the stack, whereas in non-digging mode, the stack transducer is only allowed to emit symbols when its stack head is at the top of the stack. These stack transducers have a motivation from natural-language interface applications, as they capture long-distance dependencies in syntactic, semantic, and discourse structures. We study the computational capacity for deterministic digging and non-digging stack transducers, as well as for their non-erasing and checking versions. We finally show that even for the strongest variant of stack transducers the stack languages are regular.

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