arXiv subjects

Fernando Berzal

Publications and source records attributed to Fernando Berzal.

21 records · Page 2Linked to original sources

arXiv2011

A Tool for Model-Based Language Specification

Formal languages let us define the textual representation of data with precision. Formal grammars, typically in the form of BNF-like productions, describe the language syntax, which is then annotated for syntax-directed translation and completed with semantic actions. When, apart from the textual representation of data, an explicit representation of the corresponding data structure is required, the language designer has to devise the mapping between the suitable data model and its proper language specification, and then develop the conversion procedure from the parse tree to the data model instance. Unfortunately, whenever the format of the textual representation has to be modified, changes have to propagated throughout the entire language processor tool chain. These updates are time-consuming, tedious, and error-prone. Besides, in case different applications use the same language, several copies of the same language specification have to be maintained. In this paper, we introduce a model-based parser generator that decouples language specification from language processing, hence avoiding many of the problems caused by grammar-driven parsers and parser generators.

cs.SE↗

arXiv2011

Treating Insomnia, Amnesia, and Acalculia in Regular Expression Matching

Regular expressions provide a flexible means for matching strings and they are often used in data-intensive applications. They are formally equivalent to either deterministic finite automata (DFAs) or nondeterministic finite automata (NFAs). Both DFAs and NFAs are affected by two problems known as amnesia and acalculia, and DFAs are also affected by a problem known as insomnia. Existing techniques require an automata conversion and compaction step that prevents the use of existing automaton databases and hinders the maintenance of the resulting compact automata. In this paper, we propose Parallel Finite State Machines (PFSMs), which are able to run any DFA- or NFA-like state machines without a previous conversion or compaction step. PFSMs report, online, all the matches found within an input string and they solve the three aforementioned problems. Parallel Finite State Machines require quadratic time and linear memory and they are distributable. Parallel Finite State Machines make very fast distributed regular expression matching in data-intensive applications feasible.

cs.FL↗

arXiv2011

Fence - An Efficient Parser with Ambiguity Support for Model-Driven Language Specification

Model-based language specification has applications in the implementation of language processors, the design of domain-specific languages, model-driven software development, data integration, text mining, natural language processing, and corpus-based induction of models. Model-based language specification decouples language design from language processing and, unlike traditional grammar-driven approaches, which constrain language designers to specific kinds of grammars, it needs general parser generators able to deal with ambiguities. In this paper, we propose Fence, an efficient bottom-up parsing algorithm with lexical and syntactic ambiguity support that enables the use of model-based language specification in practice.

cs.CL↗