Expressiveness of Multiple Heads in CHR

Giusto, Cinzia Di; Gabbrielli, Maurizio; Meo, Maria Chiara

doi:10.1007/978-3-540-95891-8_21

Cited by 9 publications

(18 citation statements)

References 13 publications

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“…Three main aspects affect the computational power of CHR: the number of atoms allowed in the heads, the nature of the underlying signature on which programs are defined, and the constraint theory, defining the meaning of built-ins. Some results in [32] indicate that when restricting to single headed rules the computational power of CHR decreases. However, these results consider Turing complete fragments of CHR, hence they do not establish any decidability result.…”

Section: Chr With Prioritiesmentioning

confidence: 99%

“…Indeed, single headed CHR is Turing-complete [32], provided that the host language allows functors and supports unification. On the other hand, when allowing mul-tiple heads, even restricting to a host language which allows only constants does not allow to obtain any decidability property, since also with this limitation CHR is still Turing complete [116,32].…”

Section: Chr With Prioritiesmentioning

confidence: 99%

“…On the other hand, when allowing mul-tiple heads, even restricting to a host language which allows only constants does not allow to obtain any decidability property, since also with this limitation CHR is still Turing complete [116,32]. The only (implicit) decidability results concern…”

Section: Chr With Prioritiesmentioning

confidence: 99%

“…is strictly less expressive than CHR ωa (C): in fact there exists a termination preserving encoding of Turing Machines into CHR ωa (C) [116,32].…”

Section: Definition 52 Given Two Configurations Smentioning

confidence: 99%

“…As mentioned in the introduction, while CHR ωa (C) and CHR ωa 1 (F ) are Turing complete languages [116,32], the question of the expressive power of CHR ωa 1 (C) is open. Here we answer to this question by proving that the existence of a terminating computation is decidable for this language, thus showing that CHR ωa 1 (C) is less expressive than Turing machines.…”

Section: Single-headed Chr ω a (C)mentioning

confidence: 99%

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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: Chr With Prioritiesmentioning

confidence: 99%

Section: Chr With Prioritiesmentioning

confidence: 99%

Section: Chr With Prioritiesmentioning

confidence: 99%

“…is strictly less expressive than CHR ωa (C): in fact there exists a termination preserving encoding of Turing Machines into CHR ωa (C) [116,32].…”

Section: Definition 52 Given Two Configurations Smentioning

confidence: 99%

Section: Single-headed Chr ω a (C)mentioning

confidence: 99%

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Constraints Meet Concurrency

Mauro

2014

Atlantis Studies in Computing

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Constraint Handling Rules - What Else?

Frühwirth

2015

Rule Technologies: Foundations, Tools, and Applications

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Abstract. Constraint Handling Rules (CHR) is both an effective concurrent declarative constraint-based programming language and a versatile computational formalism. While conceptually simple, CHR is distinguished by a remarkable combination of desirable features:-a semantic foundation in classical and linear logic, -an effective and efficient sequential and parallel execution model -guaranteed properties like the anytime online algorithm properties -powerful analysis methods for deciding essential program properties. This overview of some CHR-related research and applications is by no means meant to be complete. Essential introductory reading for CHR provide the survey article [125] and the books [56,63]. Up-to-date information on CHR can be found online at the CHR web-page www. constraint-handling-rules.org, including the slides of the keynote talk associated with this article. In addition, the CHR website dtai. cs.kuleuven.be/CHR/ offers everything you want to know about CHR, including online demo versions and free downloads of the language. Executive SummaryConstraint Handling Rules (CHR) [56] tries to bridge the gap between theory and practice, between logical specification and executable program by abstraction through constraints and the concepts of computational logic. CHR has its roots in constraint logic programming and concurrent constraint programming, but also integrates ideas from multiset transformation and rewriting systems as well as automated reasoning and theorem proving. It seamlessly blends multi-headed rewriting and concurrent constraint logic programming into a compact userfriendly rule-based programming language. CHR consists of guarded reactive rules that transform multisets of relations called constraints until no more change occurs. By the notion of constraint, CHR does not need to distinguish between data and operations, and its rules are both descriptive and executable.In CHR, one distinguishes two main kinds of rules: Simplification rules replace constraints by simpler constraints while preserving logical equivalence, e.g., X≤Y∧Y≤X ⇔ X=Y. Propagation rules add new constraints that are logically redundant but may cause further simplification, e.g., X≤Y∧Y≤Z ⇒ X≤Z. Together with X≤X ⇔ true, these rules encode the axioms of a partial order relation. The rules compute its transitive closure and replace inequalities ≤ by equalities = whenever possible. For example, A≤B∧B≤C∧C≤A becomes A=B∧B=C. More program examples can be found in Section 2. Semantics of CHR are discussed in Section 3.

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Turing-Complete Subclasses of CHR

Sneyers

2008

Logic Programming

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Expressiveness of Multiple Heads in CHR

Cited by 9 publications

References 13 publications

Constraints Meet Concurrency

Constraints Meet Concurrency

Constraint Handling Rules - What Else?

Turing-Complete Subclasses of CHR

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