Abstract. Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource usage functions, as it allows identifying the parts of a program that should be optimized, because of their greater impact on the total cost of program executions. We also report on our implementation of the proposed technique using the CiaoPP program analysis framework, and provide some experimental results.
Linear logic Concurrent Constraint programming (LCC) is an extension of concurrent constraint programming (CC), where the constraint system is based on Girard's linear logic instead of the classical logic. In this paper, we address the problem of program equivalence for this programming framework. For this purpose, we present a structural operational semantics for LCC based on a label transition system and investigate different notions of observational equivalences inspired by the state of art of process algebras. Then, we demonstrate that the asynchronous π-calculus can be viewed as simple syntactical restrictions of LCC. Finally, we show that LCC observational equivalences can be transposed straightforwardly to classical Concurrent Constraint languages and Constraint Handling Rules, and investigate the resulting equivalences.
Abstract. There are two somewhat contradictory ways of looking at modules in a given programming language. On the one hand, module systems are largely independent of the particulars of programming languages. On the other hand, the module constructs may interfere with the programming constructs, and may be redundant with the other scope mechanisms of a specific programming language, such as closures for instance. There is therefore a need to unify the programming concepts that are similar, and retain a minimum number of essential constructs to avoid arbitrary programming choices. In this paper, we realize this aim in the framework of linear logic concurrent constraint programming (LCC) languages. We first show how declarations and closures can be internalized as agents in a variant of LCC for which we provide precise operational and logical semantics in linear logic. Then, we show how a complete module system can be represented within LCC, and prove for it a general code protection property. Finally we study the instanciation of this scheme to the implementation of a safe module system for constraint logic programs, and conclude on the generality of this approach to programming languages with logical variables.
Abstract. Module systems are an essential feature of programming languages as they facilitate the re-use of existing code and the development of general purpose libraries. Unfortunately, there has been no consensual module system for Prolog, hence no strong development of libraries, in sharp contrast to what exists in Java for instance. One difficulty comes from the call predicate which interferes with the protection of the code, an essential task of a module system. By distinguishing the called module code protection from the calling module code protection, we review the existing syntactic module systems for Prolog. We show that no module system ensures both forms of code protection, with the noticeable exceptions of Ciao-Prolog and XSB. We then present a formal module system for logic programs with calls and closures, define its operational semantics and formally prove the code protection property. Interestingly, we also provide an equivalent logical semantics of modular logic programs without calls nor closures, which shows how they can be translated into constraint logic programs over a simple module constraint system.
This paper introduces and studies the notion of CLP projection for Constraint Handling Rules (CHR). The CLP projection consists of a naive translation of CHR programs into Constraint Logic Programs (CLP). We show that the CLP projection provides a safe operational and declarative approximation for CHR programs. We demónstrate moreover that a confluent CHR program has a least model, which is precisely equal to the least model of its CLP projection (closing henee a ten year-old conjecture by Abdenader et al.). Finally, we illustrate how the notion of CLP projection can be used in practice to apply CLP analyzers to CHR. In particular, we show results from applying AProVE to prove termination, and CiaoPP to infer both complexity upper bounds and types for CHR programs.
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