Abstract

Abstract
Tabled evaluation has been proved an effective method to improve several aspects of goal-oriented query evaluation, including termination and complexity. Several "native" implementations of tabled evaluation have been developed which offer good performance, but many of them require significant changes to the underlying Prolog implementation, including the compiler and the abstract machine. Approaches based on program transformation, which tend to minimize changes to both the Prolog compiler and the abstract machine, have also been proposed, but they often result in lower efficiency. We explore some techniques aimed at combining the best of these worlds, i.e., developing an extensible implementation which requires minimal modifications to the compiler and the abstract machine, and with reasonably good performance. Our preliminary experiments indicate promising results.

Abstract

Abstract
A consequence of ILP systems being implemented in Prolog or using Prolog libraries is that, usually, these systems use a Prolog internal database to store and manipulate data. However, in real-world problems, the original data is rarely in Prolog format. In fact, the data is often kept in Relational Database Management Systems (RDBMS) and then converted to a format acceptable by the ILP system. Therefore, a more interesting approach is to link the ILP system to the RDBMS and manipulate the data without converting it. This scheme has the advantage of being more scalable since the whole data does not need to be loaded into memory by the ILP system. In this paper we study several approaches of coupling ILP systems with RDBMS systems and evaluate their impact on performance. We propose to use a Deductive Database (DDB) system to transparently translate the hypotheses to relational algebra expressions. The empirical evaluation performed shows that the execution time of ILP algorithms can be effectively reduced using a DDB and that the size of the problems can be increased due to a non-memory storage of the data.

Abstract
We describe the MyYapDB, a deductive database system coupling the Yap Prolog compiler and the MySQL DBMS. We use our OPTYap extension of the Yap compiler, which is the first available system that can exploit parallelism from tabled logic programs. We describe the major features of the system, give a simplified description of the implementation and present a performance comparison of using static facts or accessing the facts as MySQL tuples for a simple example.

Abstract
An interesting feature of current Prolog systems is the ability to define external Prolog predicates that can be written in other languages. However, an important drawback of these interfaces is the fact that they lack some important features necessary to improve both the efficiency and the transparent integration of the Prolog system and the external predicates. Such an example is the cut operation. This operation is used quite often in Prolog programs, both for efficiency and semantic preservation. However, its use after a call to an externally defined predicate can have undesired effects. For example, if we have a pending connection to another application, or if we have memory blocks allocated by an external predicate, when a cut operation occurs, we may not be able to perform generic destruct actions, such as closing the pending connection or freeing the unnecessary memory. In this work, we propose an extension of the interface architecture that allows to associate generic user-defined functions with external predicates, in such a way that the Prolog engine transparently executes them when a cut operation occurs. We describe the implementation details of our proposal in the context of the Yap Prolog system.