Danny De Schreye

Termination of logic programs: the never-ending story

Abstract We survey termination analysis techniques for Logic Programs. We give an extensive introduction to the topic. We recall several motivations for the work, and point out the intuitions behind a number of LP-specific issues that turn up, such as: the study of different classes of programs and LP languages, of different classes of queries and of different selection rules, the difference between existential and universal termination, and the treatment of backward unification and local variables. Then, we turn to more technical aspects: the structure of the termination proofs, the selection of well-founded orderings, norms and level mappings, the inference of interargument relations, and special treatments proposed for dealing with mutual recursion. For each of these, we briefly sketch the main approaches presented in the literature, using a fixed example as a file rouge. We conclude with some comments on loop detection and cycle unification and state some open problems.

SLDNFA: An abductive procedure for abductive logic programs

Abstract We present SLDNFA, an extension of SLDNF resolution for abductive reasoning on abductive logic programs. SLDNFA solves the floundering abduction problem: nonground abductive atoms can be selected. SLDNFA also provides a partial solution for the floundering negation problem. Different abductive answers can be derived from an SLDNFA refutation; these answers provide different compromises between generality and comprehensibility. Two extensions of SLDNFA are proposed that satisfy stronger completeness results. The soundness of SLDNFA and its extensions is proved. Their completeness for minimal solutions with respect to implication, cardinality, and set inclusion is investigated. The formalization of SLDNFA presented here is an update of an older version and does not rely on skolemization of abductive atoms.

CONJUNCTIVE PARTIAL DEDUCTION: FOUNDATIONS, CONTROL, ALGORITHMS, AND EXPERIMENTS

Abstract Partial deduction in the Lloyd–Shepherdson framework cannot achieve certain optimisations which are possible by unfold/fold transformations. We introduce conjunctive partial deduction , an extension of partial deduction accommodating such optimisations, e.g., tupling and deforestation. We first present a framework for conjunctive partial deduction, extending the Lloyd–Shepherdson framework by considering conjunctions of atoms (instead of individual atoms) for specialisation and renaming. Correctness results are given for the framework with respect to computed answer semantics, least Herbrand model semantics, and finite failure semantics. Maintaining the well-known distinction between local and global control, we describe a basic algorithm for conjunctive partial deduction, and refine it into a concrete algorithm for which we prove termination. The problem of finding suitable renamings which remove redundant arguments turns out to be important, so we give an independent technique for this. A fully automatic implementation has been undertaken, which always terminates. Differences between the abstract semantics and Prologs left-to-right execution motivate deviations from the abstract technique in the actual implementation, which we discuss. The implementation has been tested on an extensive set of benchmarks which demonstrate that conjunctive partial deduction indeed pays off, surpassing conventional partial deduction on a range of small to medium-size programs, while remaining manageable in an automatic and terminating system.

Controlling generalization and polyvariance in partial deduction of normal logic programs

Given a program and some input data, partial deduction computes a specialized program handling any remaining input more efficiently.However, controlling the process well is a rather difficult problem.In this article, we elaborate global control for partial deduction:for which atoms, among possibly infinitely many, should specialized relations be produced, meanwhile guaranteeing correctness as well as termination? Our work is based on two ingredients. First, we use the concept of a characteristic tree, encapsulating specialization behavior rather than syntactic structure, to guide generalization and polyvariance, and we show how this can be done in a correct andelegant way. Second, we structure combinations of atoms and associated characteristic trees in global trees registering “causal” relationships among such pairs. This allows us to spot looming nontermination and perform proper generalization in order to avert the danger, without having to impose a depth bound on characteristic trees. The practical relevance and benefits of the work areillustrated through extensive experiments. Finally, a similar approach may improve upon current (on-line) control strategies for program transformation in general such as (positive) supercompilation of functional programs. It also seems valuable in the context of abstract interpretation to handle infinite domains of infinite height with more precision.

A general criterion for avoiding infinite unfolding during partial deduction

Well-founded orderings are a commonly used tool for proving the termination of programs. We introduce related concepts specialised to SLD-trees. Based on these concepts, we formulate formal and practical criteria for controlling the unfolding during the construction of SLD-trees that form the basis of a partial deduction. We provide algorithms that allow to use these criteria in a constructive way. In contrast to the many ad hoc techniques proposed in the literature, our technique provides both a formal and practically applicable framework.

Constraint-based termination analysis of logic programs

Current norm-based automatic termination analysis techniques for logic programs can be split up into different components: inference of mode or type information, derivation of models, generation of well-founded orders, and verification of the termination conditions themselves. Although providing high-precision results, these techniques suffer from an efficiency point of view, as several of these analyses are often performed through abstract interpretation. We present a new termination analysis which integrates the various components and produces a set of constraints that, when solvable, identifies successful termination proofs. The proposed method is both efficient and precise. The use of constraint sets enables the propagation on information over all different phases while the need for multiple analyses is considerably reduced.

Automatic finite unfolding using well-founded measures

We elaborate on earlier work proposing general criteria to control unfolding during partial deduction of logic programs. We study several techniques relying on more general and more powerful well-founded orderings. In particular, we extend our framework to incorporate lexicographical priorities between argument positions in a goal. We show that this handles some remaining deficiencies in previous methods. We emphasize the development of fully automatic algorithms for finite unfolding, avoiding the use of ad hoc techniques. Through an extensive formalization, we convey an understanding of the common principles underlying the various algorithms. Finally, we exhibit how our structure-based unfolding framework can be adapted to cope with datalog-like constant manipulating predicates in a satisfactory way.

Termination Analysis of Logic Programs Based on Dependency Graphs

This paper introduces a modular framework for termination analysis of logic programming. To this end, we adapt the notions of dependency pairs and dependency graphs (which were developed for term rewriting) to the logic programming domain. The main idea of the approach is that termination conditions for a program are established based on the decomposition of its dependency graph into its strongly connected components. These conditions can then be analysed separately by possibly different well-founded orders. We propose a constraint-based approach for automating the framework. Then, for example, termination techniques based on polynomial interpretations can be plugged in as a component to generate well-founded orders.

Logic Program Specialisation: How To Be More Specific

Standard partial deduction suffers from several drawbacks when compared to top-down abstract interpretation schemes. Conjunctive partial deduction, an extension of standard partial deduction, remedies one of those, namely the lack of side-ways information passing. But two other problems remain: the lack of success-propagation as well as the lack of inference of global success-information. We illustrate these drawbacks and show how they can be remedied by combining conjunctive partial deduction with an abstract interpretation technique known as more specific program construction. We present a simple, as well as a more refined integration of these methods. Finally we illustrate the practical relevance of this approach for some advanced applications, where it surpasses the precision of current abstract interpretation techniques.

Termination proofs for logic programs with tabling

Tabled evaluation is receiving increasing attention in the logic programming community. It avoids many of the shortcomings of SLD execution and provides a more flexible and often considerably more efficient execution mechanism for logic programs. In particular, tabled execution terminates more often than execution based on SLD-resolution. In this article, we introduce two notions of universal termination of logic programming with tabling: quasi-termination and (the stronger notion of) LG-termination. We present sufficient conditions for these two notions of termination, namely quasi-acceptability and LG-acceptability, and we show that these conditions are also necessary in case the selection of tabled predicates meets certain natural criteria. Starting from these conditions, we develop modular termination proofs, i.e., proofs capable of combining termination proofs of separate programs to obtain termination proofs of combined programs. Finally, in the presence of mode information, we state sufficient conditions which form the basis for automatically proving termination in a constraint-based way.