4,057 research outputs found
From Finite Automata to Regular Expressions and Back--A Summary on Descriptional Complexity
The equivalence of finite automata and regular expressions dates back to the
seminal paper of Kleene on events in nerve nets and finite automata from 1956.
In the present paper we tour a fragment of the literature and summarize results
on upper and lower bounds on the conversion of finite automata to regular
expressions and vice versa. We also briefly recall the known bounds for the
removal of spontaneous transitions (epsilon-transitions) on non-epsilon-free
nondeterministic devices. Moreover, we report on recent results on the average
case descriptional complexity bounds for the conversion of regular expressions
to finite automata and brand new developments on the state elimination
algorithm that converts finite automata to regular expressions.Comment: In Proceedings AFL 2014, arXiv:1405.527
Simultaneous Finite Automata: An Efficient Data-Parallel Model for Regular Expression Matching
Automata play important roles in wide area of computing and the growth of
multicores calls for their efficient parallel implementation. Though it is
known in theory that we can perform the computation of a finite automaton in
parallel by simulating transitions, its implementation has a large overhead due
to the simulation. In this paper we propose a new automaton called simultaneous
finite automaton (SFA) for efficient parallel computation of an automaton. The
key idea is to extend an automaton so that it involves the simulation of
transitions. Since an SFA itself has a good property of parallelism, we can
develop easily a parallel implementation without overheads. We have implemented
a regular expression matcher based on SFA, and it has achieved over 10-times
speedups on an environment with dual hexa-core CPUs in a typical case.Comment: This paper has been accepted at the following conference: 2013
International Conference on Parallel Processing (ICPP- 2013), October 1-4,
2013 Ecole Normale Suprieure de Lyon, Lyon, Franc
Bottom Up Quotients and Residuals for Tree Languages
In this paper, we extend the notion of tree language quotients to bottom-up
quotients. Instead of computing the residual of a tree language from top to
bottom and producing a list of tree languages, we show how to compute a set of
k-ary trees, where k is an arbitrary integer. We define the quotient formula
for different combinations of tree languages: union, symbol products,
compositions, iterated symbol products and iterated composition. These
computations lead to the definition of the bottom-up quotient tree automaton,
that turns out to be the minimal deterministic tree automaton associated with a
regular tree language in the case of the 0-ary trees
Construction of rational expression from tree automata using a generalization of Arden's Lemma
Arden's Lemma is a classical result in language theory allowing the
computation of a rational expression denoting the language recognized by a
finite string automaton. In this paper we generalize this important lemma to
the rational tree languages. Moreover, we propose also a construction of a
rational tree expression which denotes the accepted tree language of a finite
tree automaton
Performance Guarantees for Distributed Reachability Queries
In the real world a graph is often fragmented and distributed across
different sites. This highlights the need for evaluating queries on distributed
graphs. This paper proposes distributed evaluation algorithms for three classes
of queries: reachability for determining whether one node can reach another,
bounded reachability for deciding whether there exists a path of a bounded
length between a pair of nodes, and regular reachability for checking whether
there exists a path connecting two nodes such that the node labels on the path
form a string in a given regular expression. We develop these algorithms based
on partial evaluation, to explore parallel computation. When evaluating a query
Q on a distributed graph G, we show that these algorithms possess the following
performance guarantees, no matter how G is fragmented and distributed: (1) each
site is visited only once; (2) the total network traffic is determined by the
size of Q and the fragmentation of G, independent of the size of G; and (3) the
response time is decided by the largest fragment of G rather than the entire G.
In addition, we show that these algorithms can be readily implemented in the
MapReduce framework. Using synthetic and real-life data, we experimentally
verify that these algorithms are scalable on large graphs, regardless of how
the graphs are distributed.Comment: VLDB201
A General Framework for the Derivation of Regular Expressions
The aim of this paper is to design a theoretical framework that allows us to
perform the computation of regular expression derivatives through a space of
generic structures. Thanks to this formalism, the main properties of regular
expression derivation, such as the finiteness of the set of derivatives, need
only be stated and proved one time, at the top level. Moreover, it is shown how
to construct an alternating automaton associated with the derivation of a
regular expression in this general framework. Finally, Brzozowski's derivation
and Antimirov's derivation turn out to be a particular case of this general
scheme and it is shown how to construct a DFA, a NFA and an AFA for both of
these derivations.Comment: 22 page
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