arXiv subjects

Péter Szeredi

Publications and source records attributed to Péter Szeredi.

3 recordsLinked to original sources

arXiv2011

Using Constraint Handling Rules to Provide Static Type Analysis for the Q Functional Language

We describe an application of Prolog: a type checking tool for the Q functional language. Q is a terse vector processing language, a descendant of APL, which is getting more and more popular, especially in financial applications. Q is a dynamically typed language, much like Prolog. Extending Q with static typing improves both the readability of programs and programmer productivity, as type errors are discovered by the tool at compile time, rather than through debugging the program execution. The type checker uses constraints that are handled by Prolog Constraint Handling Rules. During the analysis, we determine the possible type values for each program expression and detect inconsistencies. As most built-in function names of Q are overloaded, i.e. their meaning depends on the argument types, a quite complex system of constraints had to be implemented.

cs.PL↗

arXiv2009

Efficient Description Logic Reasoning in Prolog: The DLog system

This paper describes a resolution based Description Logic reasoning system called DLog. DLog transforms Description Logic axioms into a Prolog program and uses the standard Prolog execution for efficiently answering instance retrieval queries. From the Description Logic point of view, DLog is an ABox reasoning engine for the full SHIQ language. The DLog approach makes it possible to store the individuals in a database instead of memory, which results in better scalability and helps using description logic ontologies directly on top of existing information sources. To appear in Theory and Practice of Logic Programming (TPLP).

cs.LO↗

arXiv2007

Optimizing Queries in a Logic-based Information Integration System

The SINTAGMA information integration system is an infrastructure for accessing several different information sources together. Besides providing a uniform interface to the information sources (databases, web services, web sites, RDF resources, XML files), semantic integration is also needed. Semantic integration is carried out by providing a high-level model and the mappings to the models of the sources. When executing a query of the high level model, a query is transformed to a low-level query plan, which is a piece of Prolog code that answers the high-level query. This transformation is done in two phases. First, the Query Planner produces a plan as a logic formula expressing the low-level query. Next, the Query Optimizer transforms this formula to executable Prolog code and optimizes it according to structural and statistical information about the information sources. This article discusses the main ideas of the optimization algorithm and its implementation.

cs.PL↗