Datalog as a parallel general purpose programming language

The increasing available parallelism of computers demands new programming languages that make parallel programming dramatically easier and less error prone. It is proposed that datalog with negation and timestamps is a suitable basis for a general purpose programming language for sequential, parallel and distributed computers. This paper develops a fully incremental bottom-up interpreter for datalog that supports a wide range of execution strategies, with trade-offs affecting efficiency, parallelism and control of resource usage. Examples show how the language can accept real-time external inputs and outputs, and mimic assignment, all without departing from its pure logical semantics

A Parallel semantics for normal logic programs plus time

It is proposed that Normal Logic Programs with an explicit time ordering are a suitable basis for a general purpose parallel programming language. Examples show that such a language can accept real-time external inputs and outputs, and mimic assignment, all without departing from its pure logical semantics. This paper describes a fully incremental bottom-up interpreter that supports a wide range of parallel execution strategies and can extract significant potential parallelism from programs with complex dependencies

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Looking for P Truth

In a general sense, Logic studies how to derive new pieces of in- formation from previous ones. In this paper we explore the analogies between P systems, where new configurations can be obtained from previous ones by using a set of rules, and the derivation of new theorems from previous ones or from axioms by using inference rules.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

RedAlert: Determinacy Inference for Prolog

This paper revisits the problem of determinacy inference addressing the problem of how to uniformly handle cut. To this end a new semantics is introduced for cut, which is abstracted to systematically derive a backward analysis that derives conditions sufficient for a goal to succeed at most once. The method is conceptionally simpler and easier to implement than existing techniques, whilst improving the latter's handling of cut. Formal arguments substantiate correctness and experimental work, and a tool called 'RedAlert' demonstrates the method's generality and applicability.Comment: Theory and Practice of Logic Programming, 2011, 27th Int'l. Conference on Logic Programming (ICLP'11) Special Issue, volume 11, issue 4-

Upside-down Deduction

Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods

Detecting Determinacy in Prolog Programs: 22nd International Conference, ICLP 2006, Seattle, WA, USA, August 17-20, 2006. Proceedings

In program development it is useful to know that a call to a Prolog program will not inadvertently leave a choice-point on the stack. Determinacy inference has been proposed for solving this problem yet the analysis was found to be wanting in that it could not infer determinacy conditions for programs that contained cuts or applied certain tests to select a clause. This paper shows how to remedy these serious deficiencies. It also addresses the problem of identifying those predicates which can be rewritten in a more deterministic fashion. To this end, a radically new form of determinacy inference is introduced, which is founded on ideas in ccp, that is capable of reasoning about the way bindings imposed by a rightmost goal can make a leftmost goal deterministic