8,095 research outputs found

    The Ecce and Logen Partial Evaluators and their Web Interfaces

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    We present Ecce and Logen, two partial evaluators for Prolog using the online and offline approach respectively. We briefly present the foundations of these tools and discuss various applications. We also present new implementations of these tools, carried out in Ciao Prolog. In addition to a command-line interface new user-friendly web interfaces were developed. These enable non-expert users to specialise logic programs using a web browser, without the need for a local installation

    Homeomorphic Embedding for Online Termination of Symbolic Methods

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    Well-quasi orders in general, and homeomorphic embedding in particular, have gained popularity to ensure the termination of techniques for program analysis, specialisation, transformation, and verification. In this paper we survey and discuss this use of homeomorphic embedding and clarify the advantages of such an approach over one using well-founded orders. We also discuss various extensions of the homeomorphic embedding relation. We conclude with a study of homeomorphic embedding in the context of metaprogramming, presenting some new (positive and negative) results and open problems

    A Polyvariant Binding-Time Analysis for Off-line Partial Deduction

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    We study the notion of binding-time analysis for logic programs. We formalise the unfolding aspect of an on-line partial deduction system as a Prolog program. Using abstract interpretation, we collect information about the run-time behaviour of the program. We use this information to make the control decisions about the unfolding at analysis time and to turn the on-line system into an off-line system. We report on some initial experiments.Comment: 19 pages (including appendix) Paper (without appendix) appeared in Programming Languages and Systems, Proceedings of the European Symposium on Programming (ESOP'98), Part of ETAPS'98 (Chris Hankin, eds.), LNCS, vol. 1381, 1998, pp. 27-4

    Towards Intelligent Databases

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    This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

    Proving Correctness of Imperative Programs by Linearizing Constrained Horn Clauses

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    We present a method for verifying the correctness of imperative programs which is based on the automated transformation of their specifications. Given a program prog, we consider a partial correctness specification of the form {φ}\{\varphi\} prog {ψ}\{\psi\}, where the assertions φ\varphi and ψ\psi are predicates defined by a set Spec of possibly recursive Horn clauses with linear arithmetic (LA) constraints in their premise (also called constrained Horn clauses). The verification method consists in constructing a set PC of constrained Horn clauses whose satisfiability implies that {φ}\{\varphi\} prog {ψ}\{\psi\} is valid. We highlight some limitations of state-of-the-art constrained Horn clause solving methods, here called LA-solving methods, which prove the satisfiability of the clauses by looking for linear arithmetic interpretations of the predicates. In particular, we prove that there exist some specifications that cannot be proved valid by any of those LA-solving methods. These specifications require the proof of satisfiability of a set PC of constrained Horn clauses that contain nonlinear clauses (that is, clauses with more than one atom in their premise). Then, we present a transformation, called linearization, that converts PC into a set of linear clauses (that is, clauses with at most one atom in their premise). We show that several specifications that could not be proved valid by LA-solving methods, can be proved valid after linearization. We also present a strategy for performing linearization in an automatic way and we report on some experimental results obtained by using a preliminary implementation of our method.Comment: To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201

    Constrained Query Answering

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    Traditional answering methods evaluate queries only against positive and definite knowledge expressed by means of facts and deduction rules. They do not make use of negative, disjunctive or existential information. Negative or indefinite knowledge is however often available in knowledge base systems, either as design requirements, or as observed properties. Such knowledge can serve to rule out unproductive subexpressions during query answering. In this article, we propose an approach for constraining any conventional query answering procedure with general, possibly negative or indefinite formulas, so as to discard impossible cases and to avoid redundant evaluations. This approach does not impose additional conditions on the positive and definite knowledge, nor does it assume any particular semantics for negation. It adopts that of the conventional query answering procedure it constrains. This is achieved by relying on meta-interpretation for specifying the constraining process. The soundness, completeness, and termination of the underlying query answering procedure are not compromised. Constrained query answering can be applied for answering queries more efficiently as well as for generating more informative, intensional answers

    Generalization Strategies for the Verification of Infinite State Systems

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    We present a method for the automated verification of temporal properties of infinite state systems. Our verification method is based on the specialization of constraint logic programs (CLP) and works in two phases: (1) in the first phase, a CLP specification of an infinite state system is specialized with respect to the initial state of the system and the temporal property to be verified, and (2) in the second phase, the specialized program is evaluated by using a bottom-up strategy. The effectiveness of the method strongly depends on the generalization strategy which is applied during the program specialization phase. We consider several generalization strategies obtained by combining techniques already known in the field of program analysis and program transformation, and we also introduce some new strategies. Then, through many verification experiments, we evaluate the effectiveness of the generalization strategies we have considered. Finally, we compare the implementation of our specialization-based verification method to other constraint-based model checking tools. The experimental results show that our method is competitive with the methods used by those other tools. To appear in Theory and Practice of Logic Programming (TPLP).Comment: 24 pages, 2 figures, 5 table

    Typed Norms for Typed Logic Programs

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    As typed logic programming becomes more mainstream, system building tools like partial deduction systems will need to be mapped from untyped languages to typed ones. It is important, however, when mapping techniques across that the new techniques should exploit the type system as much as possible. in this paper, we show how norms which play a crucial role in termination analysis, can be generated from the prescribed types of a logic program. Interestingly, the types highlight restrictions of earlier norms and suggest how these norms can be extended to obtain some very general and powerful notions of norm which can be used to measure any term in an almost arbitrary way. We see our work on norm derivation as a contribution to the termination analysis of typed logic programs which, in particular, forms an essential part of offline partial deduction systems

    Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

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    Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed
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