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Abstract interpretation-based model checking provides an approach to verifying properties of infinite-state systems. In practice, most previous work on abstract model checking is either restricted to verifying universal properties, or develops special techniques for temporal logics such as modal transition systems or other dual transition systems. By contrast we apply completely standard techniques for constructing abstract interpretations to the abstraction of a CTL semantic function, without restricting the kind of properties that can be verified. Furthermore we show that this leads directly to implementation of abstract model checking algorithms for abstract domains based on constraints, making use of an SMT solver.
A deterministic cycle scheduling of partitions at the operating system level is supposed for a multiprocessor system. In this paper, we propose a tool for generating such schedules. We use constraint based programming and develop methods and concepts for a combined interactive and automatic partition scheduling system. This paper is also devoted to basic methods and techniques for modeling and solving this partition scheduling problem. Initial application of our partition scheduling tool has proved successful and demonstrated the suitability of the methods used.
A constraint programming system combines two essential components: a constraint solver and a search engine. The constraint solver reasons about satisfiability of conjunctions of constraints, and the search engine controls the search for solutions by iteratively exploring a disjunctive search tree defined by the constraint program. The Monadic Constraint Programming framework gives a monadic definition of constraint programming where the solver is defined as a monad threaded through the monadic search tree. Search and search strategies can then be defined as firstclass objects that can themselves be built or extended by composable search transformers. Search transformers give a powerful and unifying approach to viewing search in constraint programming, and the resulting constraint programming system is first class and extremely flexible.
The interest in extensions of the logic programming paradigm beyond the class of normal logic programs is motivated by the need of an adequate representation and processing of knowledge. One of the most difficult problems in this area is to find an adequate declarative semantics for logic programs. In the present paper a general preference criterion is proposed that selects the ‘intended’ partial models of generalized logic programs which is a conservative extension of the stationary semantics for normal logic programs of [Prz91]. The presented preference criterion defines a partial model of a generalized logic program as intended if it is generated by a stationary chain. It turns out that the stationary generated models coincide with the stationary models on the class of normal logic programs. The general wellfounded semantics of such a program is defined as the set-theoretical intersection of its stationary generated models. For normal logic programs the general wellfounded semantics equals the wellfounded semantics.
Different properties of programs, implemented in Constraint Handling Rules (CHR), have already been investigated. Proving these properties in CHR is fairly simpler than proving them in any type of imperative programming language, which triggered the proposal of a methodology to map imperative programs into equivalent CHR. The equivalence of both programs implies that if a property is satisfied for one, then it is satisfied for the other. The mapping methodology could be put to other beneficial uses. One such use is the automatic generation of global constraints, at an attempt to demonstrate the benefits of having a rule-based implementation for constraint solvers.
In the most abstract definition of its operational semantics, the declarative and concurrent programming language CHR is trivially non-terminating for a significant class of programs. Common refinements of this definition, in closing the gap to real-world implementations, compromise on declarativity and/or concurrency. Building on recent work and the notion of persistent constraints, we introduce an operational semantics avoiding trivial non-termination without compromising on its essential features.
We present the tool Kato which is, to the best of our knowledge, the first tool for plagiarism detection that is directly tailored for answer-set programming (ASP). Kato aims at finding similarities between (segments of) logic programs to help detecting cases of plagiarism. Currently, the tool is realised for DLV programs but it is designed to handle various logic-programming syntax versions. We review basic features and the underlying methodology of the tool.
In this talk, I would like to share my experiences gained from participating in four CSP solver competitions and the second ASP solver competition. In particular, I’ll talk about how various programming techniques can make huge differences in solving some of the benchmark problems used in the competitions. These techniques include global constraints, table constraints, and problem-specific propagators and labeling strategies for selecting variables and values. I’ll present these techniques with experimental results from B-Prolog and other CLP(FD) systems.
We describe a framework to support the implementation of web-based systems to manipulate data stored in relational databases. Since the conceptual model of a relational database is often specified as an entity-relationship (ER) model, we propose to use the ER model to generate a complete implementation in the declarative programming language Curry. This implementation contains operations to create and manipulate entities of the data model, supports authentication, authorization, session handling, and the composition of individual operations to user processes. Furthermore and most important, the implementation ensures the consistency of the database w.r.t. the data dependencies specified in the ER model, i.e., updates initiated by the user cannot lead to an inconsistent state of the database. In order to generate a high-level declarative implementation that can be easily adapted to individual customer requirements, the framework exploits previous works on declarative database programming and web user interface construction in Curry.
Preface
(2010)
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. In this decade, previous workshops took place in Dresden (2008), Würzburg (2007), Vienna (2006), Ulm (2005), Potsdam (2004), Dresden (2002), Kiel (2001), and Würzburg (2000). Contributions to workshops deal with all theoretical, experimental, and application aspects of constraint programming (CP) and logic programming (LP), including foundations of constraint/ logic programming. Some of the special topics are constraint solving and optimization, extensions of functional logic programming, deductive databases, data mining, nonmonotonic reasoning, , interaction of CP/LP with other formalisms like agents, XML, JAVA, program analysis, program transformation, program verification, meta programming, parallelism and concurrency, answer set programming, implementation and software techniques (e.g., types, modularity, design patterns), applications (e.g., in production, environment, education, internet), constraint/logic programming for semantic web systems and applications, reasoning on the semantic web, data modelling for the web, semistructured data, and web query languages.