Concurrent and Reactive Constraint Programming

Gabbrielli, Maurizio; Palamidessi, Catuscia; Valencia, Frank

doi:10.1007/978-3-642-14309-0_11

Cited by 3 publications

(2 citation statements)

References 56 publications

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“…However constraints are equally well suited for modeling and supporting concurrency. In particular, concurrent computation can be seen for instance as agents that communicate and coordinate through a shared constraint store [50].…”

Section: Constraint Handling Rulesmentioning

confidence: 99%

Constraints Meet Concurrency

Mauro

2014

Atlantis Studies in Computing

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We investigate the benefits that emerge when the fields of constraint programming and concurrency meet. On one hand, constraints can be use in concurrency theory to increase the conciseness and the expressive power of concurrent languages from a pragmatic point of view. On the other hand, problems modeled by using constraints can be solved faster and more efficiently using a concurrent system. We explore both directions providing two separate lines of contribution. Firstly we study the expressive power of a concurrent language, namely Constraint Handling Rules, that supports constraints as a primitive construct. We show what features of this language make it Turing powerful. Then we propose a framework to solve constraint problems that is intended to be deployed on a concurrent system. For the development of this framework we used the concurrent language Jolie following the Service Oriented paradigm. Based on this experience, we also propose an extension to Service Oriented Languages to overcome some of their limitations and to improve the development of concurrent applications. Needless to say, I am also in debt with my coauthors:

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Section: Constraint Handling Rulesmentioning

confidence: 99%

Constraints Meet Concurrency

Mauro

2014

Atlantis Studies in Computing

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“…The starting point was the family of concurrent LP languages (see Chapter [35] In this sense, LO inherits an effect-free view of objects and does not exploit the linear logic context for state manipulation as in Lolli, since it lacks any form of scoping constructs. On the other hand, when seen as OR-concurrency directly supports a view of objects as multiset of independent units.…”

Section: Lomentioning

confidence: 99%

Proof-Theoretic and Higher-Order Extensions of Logic Programming

Momigliano

Ornaghi

2010

Lecture Notes in Computer Science

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Abstract. We review the Italian contribution to proof-theoretic and higher-order extensions of logic programming; this originated from the realization that Horn clauses lacked standard abstraction mechanisms such as higher-order programming, scoping constructs and forms of information hiding. Those extensions were based on the Deduction and Computation paradigm as formulated in Miller et al's approach [51], which built logic programming around the notion of focused uniform proofs The Italian contribution has been both foundational and applicative, in terms of language extensions, implementation techniques and usage of the new features to capture various computation models. We argue that the emphasis has now moved to the theory and practice of logical frameworks, carrying with it a better understanding of the foundations of proof search.

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Constraint Logic Programming

Gavanelli¹,

Rossi²

2010

Lecture Notes in Computer Science

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Abstract. Constraint Logic Programming (CLP) is one of the most successful branches of Logic Programming; it attracts the interest of theoreticians and practitioners, and it is currently used in many commercial applications. Since the original proposal, it has developed enormously: many languages and systems are now available either as open source programs or as commercial systems.Also, CLP has been one of the technologies able to recruit researchers from other communities to the declarative programming cause. Current CLP engines include technologies and results developed in other communities, which themselves discovered logic as an invaluable tool to model and solve real-life problems. The CLP ParadigmConstraint Logic Programming (CLP) [7] represents a successful attempt to merge the best features of logic programming (LP) and constraint solving.Constraint solving [127,6,56,31] includes a variety of expressive modelling frameworks and efficient solving tools for real-life problems that can be described via a set of variables and constraints over them. A constraint is just a restriction imposed over the combination of values of some variables of the problem. Solving a problem with constraints means finding a way to assign values to all its variables such that all constraints are satisfied. Constraint solving methods have been successfully applied to many application domains, such as scheduling, planning, resource allocation, vehicle routing, computer networks, and bioinformatics [137,127,51].Embedding the notion of constraint into a high-level programming language allows for a more flexible and practical constraint processing environment, where constraints can be represented as formulae and can be incrementally accumulated. Moreover, the presence of constraints in a programming language usually augments its expressive power, in the sense that some complex relations can be defined easily by means of constraints, and there are also efficient techniques to prove them.For these reasons, constraints have been embedded in many programming environments, but some are more suitable than others. For example, the fact that constraints can be seen as relations or predicates, that constraint solving can be seen as a generalized form of unification, that their conjunction can be seen as a logical and, and that backtracking search is the base methodology to A. Dovier, E. Pontelli (Eds.): 25

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Concurrent and Reactive Constraint Programming

Cited by 3 publications

References 56 publications

Constraints Meet Concurrency

Constraints Meet Concurrency

Proof-Theoretic and Higher-Order Extensions of Logic Programming

Constraint Logic Programming

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