Pushdown automaton

About: Pushdown automaton is a research topic. Over the lifetime, 1868 publications have been published within this topic receiving 35399 citations.

Supervisory control synthesis for deterministic context free specification languages

Abstract: This paper describes two steps in the generalization of supervisory control theory to situations where the specification is modeled by a deterministic context free language (DCFL). First, it summarizes a conceptual iterative algorithm from Schneider et al. (2014) solving the supervisory control problem for language models. This algorithm involves two basic iterative functions. Second, the main part of this paper presents an implementable algorithm realizing one of these functions, namely the calculation of the largest controllable marked sublanguage of a given DCFL. This algorithm least restrictively removes controllability problems in a deterministic pushdown automaton realizing this DCFL.

TkT: Automatic Inference of Timed and Extended Pushdown Automata

Abstract: To mitigate the cost of manually producing and maintaining models capturing software specifications, specification mining techniques can be exploited to automatically derive up-to-date models that faithfully represent the behavior of software systems. So far, specification mining solutions focused on extracting information about the functional behavior of the system, especially in the form of models that represent the ordering of the operations. Well-known examples are finite state models capturing the usage protocol of software interfaces and temporal rules specifying relations among system events. Although the functional behavior of a software system is a primary aspect of concern, there are several other non-functional characteristics that must be typically addressed jointly with the functional behavior of a software system. Efficiency is one of the most relevant characteristics. Indeed, an application that delivers the right functionalities with an inefficient implementation may fail to satisfy the expectations of its users. Interestingly, the timing behavior is strongly dependent on the functional behavior of a software system. For instance, the timing of an operation depends on the functional complexity and size of the computation that is performed. Consequently, models that combine the functional and timing behaviors, as well as their dependencies, are extremely important to precisely reason on the behavior of software systems. In this paper, we address the challenge of generating models that capture both the functional and timing behavior of a software system from execution traces. The result is the Timed k-Tail (TkT) specification mining technique, which can mine finite state models that capture such an interplay: the functional behavior is represented by the possible order of the events accepted by the transitions, while the timing behavior is represented through clocks and clock constraints of different nature associated with transitions. Our empirical evaluation with several libraries and applications shows that TkT can generate accurate models, capable of supporting the identification of timing anomalies due to overloaded environment and performance faults. Furthermore, our study shows that TkT outperforms state-of-the-art techniques in terms of scalability and accuracy of the mined models.

Descriptional Complexity of Cellular Automata and Decidability Questions.

Abstract: We study the descriptional complexity of cellular automata (CA) which are a parallel model of computation. We show that between one of the simplest cellular models, the realtime one-way CA (realtime-OCA), and "classical" models like deterministic finite automata or pushdown automata, there will be savings concerning the size of description not bounded by any recursive function, so-called nonrecursive trade-offs. Furthermore, nonrecursive trade-offs are shown to exist between certain restricted classes of cellular automata. The set of valid computations of a Turing machine can be recognized by a realtime-OCA. This implies that many decidability questions are not even semidecidable for cellular automata. There is no pumping lemma and no minimization algorithm for cellular automata. Finally, we prove that the language class accepted by realtime-OCA is incomparable to many known and well-investigated language classes.

Stochastic Parse-Tree Recognition by a Pushdown Automaton.

Abstract: We present the stochastic generalization of what is usually called correctness theorems: we guarantee that the probabilities computed operationally by the parsing algorithms are the same as those defined denotationally on the trees and forests defined by the grammar The main idea of the paper is to precisely relate the parsing strategy with a parse-tree exploration strategy: a computational path of a parsing algorithm simply performs an exploration of a parse-tree for the input portion already parsed This approach is applied in particular to Earley and Left-Corner parsing algorithms Probability computations follow parsing operations: looping problems (in rule prediction and subtree recognition) are solved by introducing probability variables (which may not be immediately evaluated) Convergence is ensured by the syntactic construction that leads to stochastic equations systems, which are solved as soon as possible Our algorithms accept any (probabilistic) CF grammar No restrictions are made such as prescribing normal form, proscribing empty rules or cyclic grammars

Expressiveness of Visibly Pushdown Transducers

Abstract: Visibly pushdown transducers (VPTs) are visibly pushdown automata extended with outputs. They have been introduced to model transformations of nested words, i.e. words with a call/return structure. As trees and more generally hedges can be linearized into (well) nested words, VPTs are a natural formalism to express tree transformations evaluated in streaming. This paper aims at characterizing precisely the expressive power of VPTs with respect to other tree transducer models.