In recent years much research and implementation effort has been devoted both to multiparadigm languages and constraint programming languages. Following up on a series of 11 workshops (WFLP) on multiparadigm languages and constraint programming, and as a result of an open call for submissions, the journal on Theory and Practice of Logic Programming is now publishing the results of the selection of the papers submitted to this special issue.

This paper describes the development of the PALS system, an implementation of Prolog capable of efficiently exploiting or-parallelism on distributed-memory platforms—specifically Beowulf clusters. PALS makes use of a novel technique, called incremental stack-splitting. The technique proposed builds on the stack-splitting approach, previously described by the authors and experimentally validated on shared-memory systems, which in turn is an evolution of the stack-copying method used in a variety of parallel logic and constraint systems—e.g., MUSE, YAP, and Penny. The PALS system is the first distributed or-parallel implementation of Prolog based on the stack-splitting method ever realized. The results presented confirm the superiority of this method as a simple yet effective technique to transition from shared-memory to distributed-memory systems. PALS extends stack-splitting by combining it with incremental copying; the paper provides a description of the implementation of PALS, including details of how distributed scheduling is handled. We also investigate methodologies to effectively support order-sensitive predicates (e.g., side-effects) in the context of the stack-splitting scheme. Experimental results obtained from running PALS on both Shared Memory and Beowulf systems are presented and analyzed.

We extend the 0-approximation of sensing actions and incomplete information in Son and Baral (2001) to action theories with static causal laws and prove its soundness with respect to the possible world semantics. We also show that the conditional planning problem with respect to this approximation is NP-complete. We then present an answer set programming based conditional planner, called ASCP, that is capable of generating both conformant plans and conditional plans in the presence of sensing actions, incomplete information about the initial state, and static causal laws. We prove the correctness of our implementation and argue that our planner is sound and complete with respect to the proposed approximation. Finally, we present experimental results comparing ASCP to other planners.

The design and implementation of an incremental copying heap garbage collector for WAM-based Prolog systems is presented. Its heap layout consists of a number of equal-sized blocks. Other changes to the standard WAM allow these blocks to be garbage collected independently. The independent collection of heap blocks forms the basis of an incremental collecting algorithm which employs copying without marking (contrary to the more frequently used mark© or mark&slide algorithms in the context of Prolog). Compared to standard semi-space copying collectors, this approach to heap garbage collection lowers in many cases the memory usage and reduces pause times. The algorithm also allows for a wide variety of garbage collection policies including generational ones. The algorithm is implemented and evaluated in the context of hProlog.

Through the Internet and the World-Wide Web, a vast number of information sources has become available, which offer information on various subjects by different providers, often in heterogeneous formats. This calls for tools and methods for building an advanced information-processing infrastructure. One issue in this area is the selection of suitable information sources in query answering. In this paper, we present a knowledge-based approach to this problem, in the setting where one among a set of information sources (prototypically, data repositories) should be selected for evaluating a user query. We use extended logic programs (ELPs) to represent rich descriptions of the information sources, an underlying domain theory, and user queries in a formal query language (here, XML-QL, but other languages can be handled as well). Moreover, we use ELPs for declarative query analysis and generation of a query description. Central to our approach are declarative source-selection programs, for which we define syntax and semantics. Due to the structured nature of the considered data items, the semantics of such programs must carefully respect implicit context information in source-selection rules, and furthermore combine it with possible user preferences. A prototype implementation of our approach has been realized exploiting the DLV KR system and its PLP front-end for prioritized ELPs. We describe a representative example involving specific movie databases, and report about experimental results.

In this paper, we present our proposal to Constraint Functional Logic Programming over Finite Domains (CFLP()) with a lazy functional logic programming language which seamlessly embodies finite domain () constraints. This proposal increases the expressiveness and power of constraint logic programming over finite domains (CLP()) by combining functional and relational notation, curried expressions, higher-order functions, patterns, partial applications, non-determinism, lazy evaluation, logical variables, types, domain variables, constraint composition, and finite domain constraints. We describe the syntax of the language, its type discipline, and its declarative and operational semantics. We also describe , an implementation for CFLP(), and a comparison of our approach with respect to CLP() from a programming point of view, showing the new features we introduce. And, finally, we show a performance analysis which demonstrates that our implementation is competitive with respect to existing CLP() systems and that clearly outperforms the closer approach to CFLP().

In answer set programming (ASP), a problem at hand is solved by (i) writing a logic program whose answer sets correspond to the solutions of the problem, and by (ii) computing the answer sets of the program using an answer set solver as a search engine. Typically, a programmer creates a series of gradually improving logic programs for a particular problem when optimizing program length and execution time on a particular solver. This leads the programmer to a meta-level problem of ensuring that the programs are equivalent, i.e., they give rise to the same answer sets. To ease answer set programming at methodological level, we propose a translation-based method for verifying the equivalence of logic programs. The basic idea is to translate logic programs P and Q under consideration into a single logic program EQT(P,Q) whose answer sets (if such exist) yield counter-examples to the equivalence of P and Q. The method is developed here in a slightly more general setting by taking the visibility of atoms properly into account when comparing answer sets. The translation-based approach presented in the paper has been implemented as a translator called lpeq that enables the verification of weak equivalence within the smodels system using the same search engine as for the search of models. Our experiments with lpeq and smodels suggest that establishing the equivalence of logic programs in this way is in certain cases much faster than naive cross-checking of answer sets.

The application of automatic transformation processes during the formal development and optimization of programs can introduce encumbrances in the generated code that programmers usually (or presumably) do not write. An example is the introduction of redundant arguments in the functions defined in the program. Redundancy of a parameter means that replacing it by any expression does not change the result. In this work, we provide methods for the analysis and elimination of redundant arguments in term rewriting systems as a model for the programs that can be written in more sophisticated languages. On the basis of the uselessness of redundant arguments, we also propose an erasure procedure which may avoid wasteful computations while still preserving the semantics (under ascertained conditions). A prototype implementation of these methods has been undertaken, which demonstrates the practicality of our approach.

We have studied the update operator ⊕1 defined for update sequences by Eiter et al. without tautologies and we have observed that it satisfies an interesting property. This property, which we call Weak Independence of Syntax (WIS), is similar to one of the postulates proposed by Alchourrón, Gärdenfors, and Makinson (AGM); only that in this case it applies to nonmonotonic logic. In addition, we consider other five additional basic properties about update programs and we show that ⊕1 satisfies them. This work continues the analysis of the AGM postulates with respect to the ⊕1 operator under a refined view that considers N2 as a monotonic logic which allows us to expand our understanding of answer sets. Moreover, N2 helped us to derive an alternative definition of ⊕1 avoiding the use of unnecessary extra atoms.

In this paper, we present a framework for the semantics and the computation of aggregates in the context of logic programming. In our study, an aggregate can be an arbitrary interpreted second order predicate or function. We define extensions of the Kripke-Kleene, the well-founded and the stable semantics for aggregate programs. The semantics is based on the concept of a three-valued immediate consequence operator of an aggregate program. Such an operator approximates the standard two-valued immediate consequence operator of the program, and induces a unique Kripke-Kleene model, a unique well-founded model and a collection of stable models. We study different ways of defining such operators and thus obtain a framework of semantics, offering different trade-offs between precision and tractability. In particular, we investigate conditions on the operator that guarantee that the computation of the three types of semantics remains on the same level as for logic programs without aggregates. Other results show that, in practice, even efficient three-valued immediate consequence operators which are very low in the precision hierarchy, still provide optimal precision.

Control flow compilation is a hybrid between classical WAM compilation and meta-call, limited to the compilation of non-recursive clause bodies. This approach is used successfully for the execution of dynamically generated queries in an inductive logic programming setting (ILP). Control flow compilation reduces compilation times up to an order of magnitude, without slowing down execution. A lazy variant of control flow compilation is also presented. By compiling code by need, it removes the overhead of compiling unreached code (a frequent phenomenon in practical ILP settings), and thus reduces the size of the compiled code. Both dynamic compilation approaches have been implemented and were combined with query packs, an efficient ILP execution mechanism. It turns out that locality of data and code is important for performance. The experiments reported in the paper show that lazy control flow compilation is superior in both artificial and real life settings.

This paper presents a property of propositional theories under the answer sets semantics (called Equilibrium Logic for this general syntax): any theory can always be reexpressed as a strongly equivalent disjunctive logic program, possibly with negation in the head. We provide two different proofs for this result: one involving a syntactic transformation, and one that constructs a program starting from the countermodels of the theory in the intermediate logic of here-and-there.

This technical note describes a monotone and continuous fixpoint operator to compute the answer sets of programs with aggregates. The fixpoint operator relies on the notion of aggregate solution. Under certain conditions, this operator behaves identically to the three-valued immediate consequence operator ΦaggrP for aggregate programs, independently proposed in Pelov (2004) and Pelov et al. (2004). This operator allows us to closely tie the computational complexity of the answer set checking and answer sets existence problems to the cost of checking a solution of the aggregates in the program. Finally, we relate the semantics described by the operator to other proposals for logic programming with aggregates.

We present in this paper a general algorithm for solving first-order formulas in particular theories called decomposable theories. First of all, using special quantifiers, we give a formal characterization of decomposable theories and show some of their properties. Then, we present a general algorithm for solving first-order formulas in any decomposable theory T. The algorithm is given in the form of five rewriting rules. It transforms a first-order formula ϕ, which can possibly contain free variables, into a conjunction φ of solved formulas easily transformable into a Boolean combination of existentially quantified conjunctions of atomic formulas. In particular, if ϕ has no free variables then φ is either the formula true or ¬true. The correctness of our algorithm proves the completeness of the decomposable theories. Finally, we show that the theory of finite or infinite trees is a decomposable theory and give some benchmarks realized by an implementation of our algorithm, solving formulas on two-partner games in with more than 160 nested alternated quantifiers.

The goal of this paper is to provide a strong integration between constraint modelling and relational DBMSs. To this end we propose extensions of standard query languages such as relational algebra and SQL, by adding constraint modelling capabilities to them. In particular, we propose non-deterministic extensions of both languages, which are specially suited for combinatorial problems. Non-determinism is introduced by means of a guessing operator, which declares a set of relations to have an arbitrary extension. This new operator results in languages with higher expressive power, able to express all problems in the complexity class NP. Some syntactical restrictions which make data complexity polynomial are shown. The effectiveness of both extensions is demonstrated by means of several examples. The current implementation, written in Java using local search techniques, is described.

We present a technique for the automated verification of abstract models of multithreaded programs providing fresh name generation, name mobility, and unbounded control. As high level specification language we adopt here an extension of communication finite-state machines with local variables ranging over an infinite name domain, called TDL programs. Communication machines have been proved very effective for representing communication protocols as well as for representing abstractions of multithreaded software. The verification method that we propose is based on the encoding of TDL programs into a low level language based on multiset rewriting and constraints that can be viewed as an extension of Petri Nets. By means of this encoding, the symbolic verification procedure developed for the low level language in our previous work can now be applied to TDL programs. Furthermore, the encoding allows us to isolate a decidable class of verification problems for TDL programs that still provide fresh name generation, name mobility, and unbounded control. Our syntactic restrictions are in fact defined on the internal structure of threads: In order to obtain a complete and terminating method, threads are only allowed to have at most one local variable (ranging over an infinite domain of names).

Combining a set of existing constraint solvers into an integrated system of cooperating solvers is a useful and economic principle to solve hybrid constraint problems. In this paper we show that this approach can also be used to integrate different language paradigms into a unified framework. Furthermore, we study the syntactic, semantic and operational impacts of this idea for the amalgamation of declarative and constraint programming.

In this paper we compare three different formalisms that can be used in the area of models for distributed, concurrent and mobile systems. In particular we analyze the relationships between a process calculus, the Fusion Calculus, graph transformations in the Synchronized Hyperedge Replacement with Hoare synchronization (HSHR) approach and logic programming. We present a translation from Fusion Calculus into HSHR (whereas Fusion Calculus uses Milner synchronization) and prove a correspondence between the reduction semantics of Fusion Calculus and HSHR transitions. We also present a mapping from HSHR into a transactional version of logic programming and prove that there is a full correspondence between the two formalisms. The resulting mapping from Fusion Calculus to logic programming is interesting since it shows the tight analogies between the two formalisms, in particular for handling name generation and mobility. The intermediate step in terms of HSHR is convenient since graph transformations allow for multiple, remote synchronizations, as required by Fusion Calculus semantics.

To alleviate the inefficiencies caused by the interaction of the logic and functional sides, integrated languages may take advantage of demand information, i.e. knowing in advance which computations are needed and, to which extent, in a particular context. This work studies demand analysis – which is closely related to backwards strictness analysis – in a semantic framework of partial predicates, which in turn are constructive realizations of ideals in a domain. This will allow us to give a concise, unified presentation of demand analysis, to relate it to other analyses based on abstract interpretation or strictness logics, some hints for the implementation, and, more important, to prove the soundness of our analysis based on demand equations. There are also some innovative results. One of them is that a set constraint-based analysis has been derived in a stepwise manner using ideas taken from the area of program transformation. The other one is the possibility of using program transformation itself to perform the analysis, specially in those domains of properties where algorithms based on constraint solving are too weak.