Salomon Sickert

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We present a new algorithm to construct a deterministic Ra-bin automaton for an LTL formula ϕ. The automaton is the product of a master automaton and an array of slave automata, one for each G-subformula of ϕ. The slave automaton for Gψ is in charge of recognizing whether FGψ holds. As opposed to standard determinization procedures, the states of all our(More)
We consider the extensions of modal transition systems (MTS), namely Boolean MTS and parametric MTS and we investigate the refinement problems over both classes. Firstly, we reduce the problem of modal refinement over both classes to a problem solvable by a QBF solver and provide experimental results showing our technique scales well. Secondly , we extend(More)
Recently a new method directly translating linear temporal logic (LTL) formulas to deterministic (generalized) Rabin automata was proposed by Javier Esparza and Jan Kretínsk´y [1]. Compared to the existing approaches of constructing a non-deterministic Buechi-automaton in the first step and then applying a determinization procedure (e.g. some variant of(More)
Controller synthesis for general linear temporal logic (LTL) objectives is a challenging task. The standard approach involves translating the LTL objective into a deterministic parity automaton (DPA) by means of the Safra-Piterman construction. One of the challenges is the size of the DPA, which often grows very fast in practice, and can reach double(More)
Modal transition systems (MTS) is a well-studied specification formalism of reactive systems supporting a step-wise refinement methodology. Despite its many advantages, the formalism as well as its currently known extensions are incapable of expressing some practically needed aspects in the refinement process like exclusive, conditional and persistent(More)
Automatic recognition of biological structures like membranes or synapses is important to analyze organic processes and to understand their functional behavior. To achieve this, volumetric images taken by electron microscopy or computer tomography have to be segmented into meaningful semantic regions. We are extending iterative context forests which were(More)
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