5,865 research outputs found
First-order definable string transformations
The connection between languages defined by computational models and logic
for languages is well-studied. Monadic second-order logic and finite automata
are shown to closely correspond to each-other for the languages of strings,
trees, and partial-orders. Similar connections are shown for first-order logic
and finite automata with certain aperiodicity restriction. Courcelle in 1994
proposed a way to use logic to define functions over structures where the
output structure is defined using logical formulas interpreted over the input
structure. Engelfriet and Hoogeboom discovered the corresponding "automata
connection" by showing that two-way generalised sequential machines capture the
class of monadic-second order definable transformations. Alur and Cerny further
refined the result by proposing a one-way deterministic transducer model with
string variables---called the streaming string transducers---to capture the
same class of transformations. In this paper we establish a transducer-logic
correspondence for Courcelle's first-order definable string transformations. We
propose a new notion of transition monoid for streaming string transducers that
involves structural properties of both underlying input automata and variable
dependencies. By putting an aperiodicity restriction on the transition monoids,
we define a class of streaming string transducers that captures exactly the
class of first-order definable transformations.Comment: 31 page
FO-definable transformations of infinite strings
The theory of regular and aperiodic transformations of finite strings has
recently received a lot of interest. These classes can be equivalently defined
using logic (Monadic second-order logic and first-order logic), two-way
machines (regular two-way and aperiodic two-way transducers), and one-way
register machines (regular streaming string and aperiodic streaming string
transducers). These classes are known to be closed under operations such as
sequential composition and regular (star-free) choice; and problems such as
functional equivalence and type checking, are decidable for these classes. On
the other hand, for infinite strings these results are only known for
-regular transformations: Alur, Filiot, and Trivedi studied
transformations of infinite strings and introduced an extension of streaming
string transducers over -strings and showed that they capture monadic
second-order definable transformations for infinite strings. In this paper we
extend their work to recover connection for infinite strings among first-order
logic definable transformations, aperiodic two-way transducers, and aperiodic
streaming string transducers
Streaming Tree Transducers
Theory of tree transducers provides a foundation for understanding
expressiveness and complexity of analysis problems for specification languages
for transforming hierarchically structured data such as XML documents. We
introduce streaming tree transducers as an analyzable, executable, and
expressive model for transforming unranked ordered trees in a single pass.
Given a linear encoding of the input tree, the transducer makes a single
left-to-right pass through the input, and computes the output in linear time
using a finite-state control, a visibly pushdown stack, and a finite number of
variables that store output chunks that can be combined using the operations of
string-concatenation and tree-insertion. We prove that the expressiveness of
the model coincides with transductions definable using monadic second-order
logic (MSO). Existing models of tree transducers either cannot implement all
MSO-definable transformations, or require regular look ahead that prohibits
single-pass implementation. We show a variety of analysis problems such as
type-checking and checking functional equivalence are solvable for our model.Comment: 40 page
Aperiodic String Transducers
Regular string-to-string functions enjoy a nice triple characterization
through deterministic two-way transducers (2DFT), streaming string transducers
(SST) and MSO definable functions. This result has recently been lifted to FO
definable functions, with equivalent representations by means of aperiodic 2DFT
and aperiodic 1-bounded SST, extending a well-known result on regular
languages. In this paper, we give three direct transformations: i) from
1-bounded SST to 2DFT, ii) from 2DFT to copyless SST, and iii) from k-bounded
to 1-bounded SST. We give the complexity of each construction and also prove
that they preserve the aperiodicity of transducers. As corollaries, we obtain
that FO definable string-to-string functions are equivalent to SST whose
transition monoid is finite and aperiodic, and to aperiodic copyless SST
Regular Combinators for String Transformations
We focus on (partial) functions that map input strings to a monoid such as
the set of integers with addition and the set of output strings with
concatenation. The notion of regularity for such functions has been defined
using two-way finite-state transducers, (one-way) cost register automata, and
MSO-definable graph transformations. In this paper, we give an algebraic and
machine-independent characterization of this class analogous to the definition
of regular languages by regular expressions. When the monoid is commutative, we
prove that every regular function can be constructed from constant functions
using the combinators of choice, split sum, and iterated sum, that are analogs
of union, concatenation, and Kleene-*, respectively, but enforce unique (or
unambiguous) parsing. Our main result is for the general case of
non-commutative monoids, which is of particular interest for capturing regular
string-to-string transformations for document processing. We prove that the
following additional combinators suffice for constructing all regular
functions: (1) the left-additive versions of split sum and iterated sum, which
allow transformations such as string reversal; (2) sum of functions, which
allows transformations such as copying of strings; and (3) function
composition, or alternatively, a new concept of chained sum, which allows
output values from adjacent blocks to mix.Comment: This is the full version, with omitted proofs and constructions, of
the conference paper currently in submissio
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