ω-automaton

About: ω-automaton is a research topic. Over the lifetime, 2299 publications have been published within this topic receiving 68468 citations. The topic is also known as: stream automaton & ω-automata.

Revisiting State Blow-Up: Automatically Building Augmented-FA While Preserving Functional Equivalence

Abstract: Regular expression matching, a central task in deep packet inspection and other networking applications, has been traditionally implemented through finite automata. Thanks to their limited per-character processing and memory bandwidth requirements, deterministic finite automata (DFA) are a natural choice for memory-based implementations. In the presence of large datasets of complex patterns, however, DFA suffer from the well-known state explosion problem. Specifically, state explosion can take place during DFA generation when the considered patterns contain bounded and unbounded repetitions of wildcards or large character sets. Several alternative FA representations have been proposed to address this problem. However, these proposals all suffer from one or more of the following problems: some can avoid state explosion only on datasets of limited size and complexity; some have prohibitive worst-case memory bandwidth requirements or processing time; and some can only guarantee functional equivalence for restricted classes of regular expressions and require the user to manually filter out unsupported patterns. In this work we propose JFA, a finite automation that uses state variables to avoid state explosion, and is functionally equivalent to the corresponding DFA. Functional equivalence is guaranteed by construction without requiring user intervention. We also provide optimization techniques to both limit the amount of state variables required and provide a lower bound for the JFA traversal time.

Improved algorithms for the automata-based approach to model-checking

Abstract: We propose and evaluate new algorithms to support the automata-based approach to model-checking: algorithms to solve the universality and language inclusion problems for nondeterministic Buchi automata. To obtain those new algorithms, we establish the existence of pre-orders that can be exploited to efficiently evaluate fixed points on the automata defined during the complementation step (that we keep implicit in our approach). We evaluate the performance of our new algorithm to check for universality of Buchi automata experimentally using the random automaton model recently proposed by Tabakov and Vardi. We show that on the difficult instances of this probabilistic model, our algorithm outperforms the standard ones by several orders of magnitude. This work is an extension to the infinite words case of new algorithms for the finite words case that we and co-authors have presented in a recent paper [DDHR06].

An Extension of Data Automata that Captures XPath

Abstract: We define a new kind of automata recognizing properties of data words or data trees and prove that the automata capture all queries definable in Regular XPath. We show that the automata-theoretic approach may be applied to answer decidability and expressibility questions for XPath. Finally, we use the newly introduced automata as a common framework to classify existing automata on data words and trees, including data automata, register automata and alternating register automata.