Abstract Interpretation Of Logic Programs Research Articles

A framework for the integration of partial evaluation and abstract interpretation of logic programs

Recently the relationship between abstract interpretation and program specialization has received a lot of scrutiny, and the need has been identified to extend program specialization techniques so as to make use of more refined abstract domains and operators. This article clarifies this relationship in the context of logic programming, by expressing program specialization in terms of abstract interpretation. Based on this, a novel specialization framework, along with generic correctness results for computed answers and finite failure under SLD-resolution, is developed.This framework can be used to extend existing logic program specialization methods, such as partial deduction and conjunctive partial deduction, to make use of more refined abstract domains. It is also shown how this opens up the way for new optimizations. Finally, as shown in the paper, the framework also enables one to prove correctness of new or existing specialization techniques in a simpler manner.The framework has already been applied in the literature to develop and prove correct specialization algorithms using regular types, which in turn have been applied to the verification of infinite state process algebras.

Denotational abstract interpretation of logic programs

Logic-programming languages are based on a principle of separation “logic” and “control.”. This means that they can be given simple model-theoretic semantics without regard to any particular execution mechanism (or proof procedure, viewing execution as theorem proving). Although the separation is desirable from a semantical point of view, it makes sound, efficient implementation of logic-programming languages difficult. The lack of “control information” in programs calls for complex data-flow analysis techniques to guide execution. Since data-flow analysis furthermore finds extensive use in error-finding and transformation tools, there is a need for a simple and powerful theory of data-flow analysis of logic programs. This paper offers such a theory, based on F. Nielson's extension of P. Cousot and R. Cousot's abstract interpretation . We present a denotational definition of the semantics of definite logic programs. This definition is of interest in its own right because of its compactness. Stepwise we develop the definition into a generic data-flow analysis that encompasses a large class of data-flow analyses based on the SLD execution model. We exemplify one instance of the definition by developing a provably correct groundness analysis to predict how variables may be bound to ground terms during execution. We also discuss implementation issues and related work.

Bottom-up abstract interpretation of logic programs

This paper presents a formal framework for the bottom-up abstract interpretation of logic programs which can be applied to approximate answer substitutions, partial answer substitutions and call patterns for a given program and arbitrary initial goal. The framework is based on a T p -like semantics defined over a Herbrand universe with variables which has previously been shown to determine the answer substitutions for arbitrary initial goals. The first part of the paper reconstructs this semantics to provide a more adequate initial goals. The first part of the paper reconstructs this semantics to provide a more adequate basis for abstract interpretation. A notion of abstract substitution is introduced and shown to determine an abstract semantic function which for a given program can be applied to approximate the answer substitutions for an arbitrary initial goal. The second part of the paper extends the bottom-up approach to provide approximations of both partial answer substitutions and call patterns. This is achieved by applying Magic Sets and other existing techniques to transform a program in such a way that the answer substitutions of the transformed program correspond to the partial answer substitutions and call patterns of the original program. This facilitates the analysis of concurrent logic programs (ignoring synchronization) and provides a collecting semantics which characterizes both success and call patterns.

A general framework for semantics-based bottom-up abstract interpretation of logic programs

The theory of abstract interpretation provides a formal framework to develop advanced dataflow analysis tools. The idea is to define a nonstandard semantics which is able to compute, in finite time, an approximated model of the program. In this paper, we define an abstract interpretation framework based on a fixpoint approach to the semantics. This leads to the definition, by means of a suitable set of operators, of an abstract fixpoint characterization of a model associated with the program. Thus, we obtain a specializable abstract framework for bottom-up abstract interpretations of definite logic programs. The specialization of the framework is shown on two examples, namely, gound-dependence analysis and depth-kanalysis.

Abstract interpretation of logic programs

article Abstract interpretation of logic programs: an abstract domain for groundness, sharing, freeness and compoundness analysis Share on Authors: Agostino Cortesi Dept. of Mathematics, University of Padova, Via Belzoni 7, I-35131 Padova, Italy Dept. of Mathematics, University of Padova, Via Belzoni 7, I-35131 Padova, ItalyView Profile , Gilbert Filé Dept. of Mathematics, University of Padova, Via Belzoni 7, I-35131 Padova, Italy Dept. of Mathematics, University of Padova, Via Belzoni 7, I-35131 Padova, ItalyView Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 26Issue 9Sept. 1991 pp 52–61https://doi.org/10.1145/115866.115872Online:01 May 1991Publication History 23citation293DownloadsMetricsTotal Citations23Total Downloads293Last 12 Months6Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access