Michael Codish

Propagation via lazy clause generation

Finite domain propagation solvers effectively represent the possible values of variables by a set of choices which can be naturally modelled as Boolean variables. In this paper we describe how to mimic a finite domain propagation engine, by mapping propagators into clauses in a SAT solver. This immediately results in strong nogoods for finite domain propagation. But a naive static translation is impractical except in limited cases. We show how to convert propagators to lazy clause generators for a SAT solver. The resulting system introduces flexibility in modelling since variables are modelled dually in the propagation engine and the SAT solver, and we explore various approaches to the dual modelling. We show that the resulting system solves many finite domain problems significantly faster than other techniques.

A semantic basis for the termination analysis of logic programs

Abstract This paper presents a formal semantic basis for the termination analysis of logic programs. The semantics exhibits the termination properties of a logic program through its binary unfoldings — a possibly infinite set of binary clauses. Termination of a program P and goal G is determined by the absence of an infinite chain in the binary unfoldings of P starting with G . The result is of practical use as basing termination analysis on a formal semantics facilitates both the design and implementation of analyzers. A simple Prolog interpreter for binary unfoldings coupled with an abstract domain based on symbolic norm constraints is proposed as an implementation vehicle. We illustrate its application using two recently proposed abstract domains. Both the techniques are implemented using a standard CLP(R) library. The combination of an interpreter for binary unfoldings and a constraint solver simplifies the design of the analyzer and improves its efficiency significantly.

Termination Analysis of Java Bytecode

Termination analysis has received considerable attention, traditionally in the context of declarative programming, and recently also for imperative languages. In existing approaches, termination is performed on source programs. However, there are many situations, including mobile code, where only the compiled code is available. In this work we present an automatic termination analysis for sequential Java Bytecode programs. Such analysis presents all of the challenges of analyzing a low-level language as well as those introduced by object-oriented languages. Interestingly, given a bytecode program, we produce a constraint logicprogram, CLP, whose termination entails termination of the bytecode program. This allows applying the large body of work in termination of CLP programs to termination of Java bytecode. A prototype analyzer is described and initial experimentation is reported.

Termination analysis of logic programs through combination of type-based norms

This article makes two contributions to the work on semantics-based termination analysis for logic programs. The first involves a novel notion of type-based norm where for a given type, a corresponding norm is defined to count in a term the number of subterms of that type. This provides a collection of candidate norms, one for each type defined in the program. The second enables an analyzer to base termination proofs on the combination of several different norms. This is useful when different norms are better suited to justify the termination of different parts of the program. Application of the two contributions together consists in considering the combination of the type-based candidate norms for a given program. This results in a powerful and practical technique. Both contributions have been introduced into a working termination analyzer. Experimentation indicates that they yield state-of-the-art results in a fully automatic analysis tool, improving with respect to methods that do not use both types and combined norms.

Specialisation of Prolog and FCP programs using abstract interpretation

This paper presents an approach to specialising logic programs which is based on abstract interpretation. Program specialisation involves two stages, the construction of an abstract computation tree and a program construction stage. For the tree construction stage, abstract OLDT resolution is defined and used to construct a complete and finite tree corresponding to a given logic program and a goal. In the program construction stage, a specialised program is extracted from this tree.We focus on two logic programming languages: sequential Prolog and Flat Concurrent Prolog. Although the procedural reading of concurrent logic programs is very different from that of sequential programs, the techniques presented provide a uniform approach to the specialisation of both languages. We present the results for Prolog rigorously, and extend them less formally to Flat Concurrent Prolog.There are two main advantages of basing program specialisation on abstract interpretation. Firstly, termination can be ensured by using abstract interpretations over finite domains, while performing a complete flow analysis of the program. Secondly, correctness of the specialised program is closely related to well-defined consistency conditions on the concrete and abstract interpretations.

Compositional analysis of modular logic programs

This paper describes a semantic basis for a compositional approach to the analysis of logic programs. A logic program is viewed as consisting of a set of modules, each module defining a subset of the programs predicates. Analyses are constructed by considering abstract interpretations of a compositional semantics. The abstract meaning of a module corresponds to its analysis and composition of abstract meanings corresponds to composition of analyses. Such an approach is essential for large program development so that altering one module does not require re-analysis of the entire program. We claim that for a substantial class of programs, compositional analyses which are based on a notion of abstract unfolding provide the same precision as non-compositional analysis. A compositional analysis for ground dependencies is included to illustrate the approach. To the best of our knowledge this is the first account of a compositional framework for the analysis of logic programs.

Testing for termination with monotonicity constraints

Termination analysis is often performed over the abstract domains of monotonicity constraints or of size change graphs. First, the transition relation for a given program is approximated by a set of descriptions. Then, this set is closed under a composition operation. Finally, termination is determined if all of the idempotent loop descriptions in this closure have (possibly different) ranking functions. This approach is complete for size change graphs: An idempotent loop description has a ranking function if and only if it has one which indicates that some specific argument decreases in size. In this paper we generalize the size change criteria for size change graphs which are not idempotent. We also illustrate that proving termination with monotonicity constraints is more powerful than with size change graphs and demonstrate that the size change criteria is incomplete for monotonicity constraints. Finally, we provide a complete termination test for monotonicity constraints.

Bottom-up abstract interpretation of logic programs

Abstract 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 Tp-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.

Analyzing logic programs using “prop”-ositional logic programs and a magic wand

Abstract This paper illustrates the role of a class of “prop”-ositional logic programs in the analysis of complex properties of logic programs. Analyses are performed by abstracting Prolog programs to corresponding “prop”-ositional logic programs which approximate the original programs and have finite meanings. We focus on a groundness analysis which is equivalent to that obtained by abstract interpretation using the domain Prop . The main contribution is in the ease in which a highly efficient implementation of the analysis is obtained. The implementation is bottom-up and provides approximations of a programs success patterns . Goal-dependent information such as call patterns is obtained using a magic-set transformation. A novel compositional approach is applied so that call patterns for arbitrary goals are derived in a precise and efficient way.

Sharing and groundness dependencies in logic programs

We investigate Jacobs and Langens Sharing domain, introduced for the analysis of variable sharing in logic programs, and show that it is isomorphic to Marriott and Søndergaards Pos domain, introduced for the analysis of groundness dependencies. Our key idea is to view the sets of variables in a Sharing domain element as the models of a corresponding Boolean function. This leads to a recasting of sharing analysis in terms of the property of “not being affected by the binding of a single variable.” Such an “unaffectedness dependency” analysis has close connections with groundness dependency analysis using positive Boolean functions. This new view improves our understanding of sharing analysis, and leads to an elegant expression of its combination with groundness dependency analysis based on the reduced product of Sharing and Pos. It also opens up new avenues for the efficient implementation of sharing analysis, for example using reduced order binary decision diagrams, as well as efficient implementation of the reduced product, using domain factorizations.