Value withdrawal explanations: a theoretical tool for programming environments

Constraint logic programming combines declarativity and efficiency thanks to constraint solvers implemented for specific domains. Value withdrawal explanations have been efficiently used in several constraints programming environments but there does not exist any formalization of them. This paper is an attempt to fill this lack. Furthermore, we hope that this theoretical tool could help to validate some programming environments. A value withdrawal explanation is a tree describing the withdrawal of a value during a domain reduction by local consistency notions and labeling. Domain reduction is formalized by a search tree using two kinds of operators: operators for local consistency notions and operators for labeling. These operators are defined by sets of rules. Proof trees are built with respect to these rules. For each removed value, there exists such a proof tree which is the withdrawal explanation of this value.Comment: 14 pages; Alexandre Tessier, editor; WLPE 2002, http://xxx.lanl.gov/abs/cs.SE/020705

Towards declarative diagnosis of constraint programs over finite domains

The paper proposes a theoretical approach of the debugging of constraint programs based on a notion of explanation tree. The proposed approach is an attempt to adapt algorithmic debugging to constraint programming. In this theoretical framework for domain reduction, explanations are proof trees explaining value removals. These proof trees are defined by inductive definitions which express the removals of values as consequences of other value removals. Explanations may be considered as the essence of constraint programming. They are a declarative view of the computation trace. The diagnosis consists in locating an error in an explanation rooted by a symptom.Comment: In M. Ronsse, K. De Bosschere (eds), proceedings of the Fifth International Workshop on Automated Debugging (AADEBUG 2003), September 2003, Ghent. cs.SE/030902

Explanations and Proof Trees

This paper proposes a model for explanations in a set theoretical framework using the notions of closure or fixpoint. In this approach, sets of rules associated with monotonic operators allow to define proof trees. The proof trees may be considered as a declarative view of the trace of a computation. We claim they are explanations of the results of a computation. This notion of explanation is applied to constraint logic programming, and it is used for declarative error diagnosis. It is also applied to constraint programming, and used for constraint retraction

Explications de retraits de valeurs en programmation par contraintes et application au diagnostic déclaratif

La programmation par contraintes sur domaines finis a montré son efficacité pour traiter les problèmes difficiles, tant au point de vue de leur modélisation que de leur résolution. Les solveurs utilisés pour obtenir leurs solutions mêlent des techniques de réduction de domaine à des techniques d'énumération et commencent à utiliser des notions d'explications. Cette thèse propose trois contributions au domaine de la programmation par contraintes. Tout d'abord la réduction de domaine est reformulée en terme ensembliste et vue comme un calcul de point fixe. Ensuite, ce cadre permet une définition naturelle et générale d'explication, appelée arbre explicatif. Ces arbres de preuve sont inductivement définis par des règles exprimant le retrait d'une valeur comme conséquence d'autres retraits. Enfin, la vision des arbres explicatifs en tant que trace déclarative du calcul permet de les utiliser pour adapter le diagnostic déclaratif de réponse manquante à la programmation par contraintes.ORLEANS-BU Sciences (452342104) / SudocSudocFranceF

Theoretical Foundations of Value Withdrawal Explanations for Domain Reduction

Solvers on finite domains use local consistency notions to remove values from the domains. This paper defines value withdrawal explanations. Domain reduction is formalized with chaotic iterations of monotonic operators. To each operator is associated its dual which will be described by a set of rules. For classical consistency notions, there exists a natural such system of rules. They express value removals as consequences of other value removals. The linking of these rules inductively defines proof trees. Such a proof tree clearly explains the removal of a value (the root of the tree). Explanations can be considered as the essence of domain reduction

Clustering conceptuel et relationnel en programmation par contraintes

National audienceDifférentes tâches de clustering existent dans le domaine de la fouille de données. Le clustering conceptuel pour les données qualitatives vise à identifier des concepts, les clusters sont alors définis par ces concepts. Le clustering relationnel cherche à partitionner les données dans des clusters homogènes et/ou bien séparés à partir d'une mesure de dissimilarité entre les objets. Des travaux récents ont proposé des cadres généraux et déclaratifs fondés sur la programmation par contraintes pour le clustering conceptuel ou pour le clustering relationnel. Dans ce papier, nous proposons un cadre plus général qui unifie les clusterings conceptuel et relationnel en programmation par contraintes.Ce cadre permet de tirer avantage des deux approches, en optimisant un critère relationnel ou conceptuel et en intégrant des contraintes qu'elles soient de structure, qu'elles portent sur les distances entre les objets ou sur leurs propriétés communes. Nous proposons de plus un modèle amélioré pour traiter les contraintes conceptuelles reposant sur des contraintes ensemblistes

Property grammar parsing seen as a constraint optimization problem

Abstract. Blache [3] proposed a model-theoretic semantics for property grammar. The present paper follows up on that work and explains how to turn such a formalization into a constraint optimization problem, solvable using constraint programming techniques. This naturally leads to an implementation of a fully constraint-based parser for property grammars