LR parsing techniques have long been studied as efficient and powerful methods for processing context free languages. A linear time algorithm for recognizing languages representable by LR(k) grammars has long been known. Recognizing substrings of a context-free language is at least as hard as recognizing full strings of the language, as the latter problem easily reduces to the former. In this paper we present a linear time algorithm for recognizing substrings of LR(k) languages, thus showing that the substring recognition problem for these languages is no harder than the full string recognition problem. An interesting data structure, the Forest Structured Stack, allows the algorithm to track all possible parses of a substring without loosing the efficiency of the original LR parser. We present the algorithm, prove its correctness, analyze its complexity, and mention several applications that have been constructed. 1 Introduction The problem of recognizing substrings of contextfree la...

Document archives contain large amounts of data to which sophisticated queries are applied. The size of archives and the complexity of evaluating queries makes the use of parallelism attractive. The use of semantically-based markup such as SGML makes it possible to represent documents and document archives as data types. We present a theory of trees and tree homomorphisms, modelling structured text archives and operations on them, from which it can be seen that: ffl many apparently-unrelated tree operations are homomorphisms; ffl homomorphisms can be described in a simple parameterised way that gives standard sequential and parallel implementations for them; ffl special classes of homomorphisms have parallel implementations of practical interest. In particular, we develop an implementation for path expression search, a novel powerful query facility for structured text, that takes time logarithmic in the text size. Keywords: structured text, categorical data type, software developme...

This report describes research done in the context of a subproject of the HPCN project IMPACT. The IMPACT project is headed by the ING bank and is founded by the organization for High Performance Computing and Networking (HPCN). The aim of the specific subproject, in the context of which this report has been written, is to develop (techniques for) natural language interfaces to information resources, focusing on the use of high-performance computers to achieve acceptable response times. This report is part of the "Parallel Parsing I" research topic. IMPACT-NLI-1997-1 ii Preface IMPACT IMPACT-NLI-1997-1 IMPACT iii Contents Preface i 1 Introduction 1 2 Basics 3

We present a concurrent compiler for Active Oberon built itself with active objects. We describe the experience made on parallelizing the Oberon compiler, in particular explaining how concurrency and synchronization are achieved by using active objects, and showing how we achieved ensured deadlock freedom. Based on the implementation, we discuss why we consider active objects beneficial for the implementation of software frameworks and where their limitations are.

Parallelism is useful in the storage and access of structured documents. Fast parallel algorithms for search in structured text are already known, but they will not supplant the use of indexes to speed up searching until massively parallel architectures become routinely available. However, parallel algorithms suggest new kinds of indexes that provide powerful search capability and performance even on modestly-parallel computers. We present a generalisation of indexes based on regular languages, called indexing languages, that are chosen to be homomorphic images of languages generated by typical search patterns. Precomputing properties of text strings relative to indexing languages makes it fast to exclude large parts of the text from consideration before executing a direct search. 1 Background Search times in document archives are improved by building indexes giving the location of (usually) words as offsets in the structure. This kind of index has three major drawbacks: it is expens...