Termination Analysis of CHR Revisited

Pilozzi, Paolo; Schreye, Danny De

doi:10.1007/978-3-540-89982-2_43

Cited by 12 publications

(17 citation statements)

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“…In theory, CHRs could be treated as an instance of an abstract rewriting system. However, the fact that matching involves more than one constraint at once sets them apart from other rewriting systems: both confluence (Abdennadher 1997;Duck et al 2007) and termination (Voets et al 2008;Pilozzi and De Schreye 2008) require specific techniques. In this section we study the applicability of those techniques to our setting.…”

Section: Confluence and Termination Propertiesmentioning

confidence: 99%

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Constraint handling rules with binders, patterns and generic quantification

Serrano¹,

Hage²

2017

Theory and Practice of Logic Programming

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Constraint Handling Rules provide descriptions for constraint solvers. However, they fall short when those constraints specify some binding structure, like higher-rank types in a constraintbased type inference algorithm. In this paper, the term syntax of constraints is replaced by λ-tree syntax, in which binding is explicit; and a new ∇ generic quantifier is introduced, which is used to create new fresh constants. This paper is under consideration for publication in TPLP. * This work was supported by the Netherlands Organisation for Scientific Research (NWO) project on "DOMain Specific Type Error Diagnosis (DOMSTED)" (612.001.213). 1 Since CHRs are Turing-complete (Sneyers et al. 2009), in theory any algorithm can be described. This does not mean that the description is convenient, though.

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Section: Confluence and Termination Propertiesmentioning

confidence: 99%

“…A rigid | · | is invariant under substitution: for all constraints C and substitutions θ, |C| = |θC|. We can redefine this notion in such a way that the techniques of (Frühwirth 2000;Voets et al 2008;Pilozzi and De Schreye 2008) keep working:…”

Section: See Appendixmentioning

confidence: 99%

Constraint handling rules with binders, patterns and generic quantification

Serrano¹,

Hage²

2017

Theory and Practice of Logic Programming

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“…To prove Ground Termination we can rely on the existing state-of-the-art work on termination for CHR programs, such as (Frühwirth 2000) and (Pilozzi and Schreye 2008). For example, we can prove that the rule (F [a] b ⇐⇒ b = [c], F a c) is ground terminating by defining rank ([x]) = 1 + rank (x).…”

Section: Relaxed Conditions To Guarantee Soundness For Terminating Goalsmentioning

confidence: 99%

On Termination, Confluence and Consistent CHR-based Type Inference

Duck

Haemmerlé

Sulzmann³

2014

Theory and Practice of Logic Programming

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We consider the application of Constraint Handling Rules (CHR) for the specification of type inference systems, such as that used by Haskell. Confluence of CHR guarantees that the answer provided by type inference is correct and consistent. The standard method for establishing confluence relies on an assumption that the CHR program is terminating. However, many examples in practice give rise to non-terminating CHR programs, rendering this method inapplicable. Despite no guarantee of termination or confluence, the Glasgow Haskell Compiler (GHC) supports options that allow the user to proceed with type inference anyway, e.g. via the use of the UndecidableInstances flag. In this paper we formally identify and verify a set of relaxed criteria, namely range-restrictedness, local confluence, and ground termination, that ensure the consistency of CHR-based type inference that maps to potentially non-terminating CHR programs

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“…In particular, type information is useful in this context. When used as a basis for determining the possible calls to the program, it leads to compiler optimisations [11], more precise termination conditions [4,7] and more refined interpretations for proving termination [1,9].…”

Section: Introductionmentioning

confidence: 99%

A Transformational Approach for Proving Properties of the CHR Constraint Store

Pilozzi

Schrijvers

Bruynooghe

2010

Logic-Based Program Synthesis and Transformation

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Abstract. Proving termination of, or generating efficient control for Constraint Handling Rules (CHR) programs requires information about the kinds of constraints that can show up in the CHR constraint store. In contrast to Logic Programming (LP), there are not many tools available for deriving such information for CHR. Hence, instead of building analyses for CHR from scratch, we define a transformation from CHR to Prolog and reuse existing analysis tools for Prolog. The proposed transformation has been implemented and combined with PolyTypes 1.3, a type analyser for Prolog, resulting in an accurate description of the types of CHR programs. Moreover, the transformation is not limited to type analysis. It can also be used to prove other properties of the constraints showing up in constraint stores, using tools for Prolog.

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Termination Analysis of CHR Revisited

Cited by 12 publications

References 11 publications

Constraint handling rules with binders, patterns and generic quantification

Constraint handling rules with binders, patterns and generic quantification

On Termination, Confluence and Consistent CHR-based Type Inference

A Transformational Approach for Proving Properties of the CHR Constraint Store

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