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30
TransformationBased BottomUp Computation of the WellFounded Model
, 1997
"... . We present a bottomup algorithm for the computation of the wellfounded model of nondisjunctive logic programs. Our method is based on the elementary program transformations studied by Brass and Dix [6, 7]. However, their "residual program" can grow to exponential size, whereas for fu ..."
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Cited by 51 (4 self)
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. We present a bottomup algorithm for the computation of the wellfounded model of nondisjunctive logic programs. Our method is based on the elementary program transformations studied by Brass and Dix [6, 7]. However, their "residual program" can grow to exponential size, whereas for functionfree programs our "program remainder " is always polynomial in the size, i.e. the number of tuples, of the extensional database (EDB). As in the SLGresolution of Chen and Warren [11, 12, 13], we do not only delay negative but also positive literals if they depend on delayed negative literals. When disregarding goaldirectedness, which needs additional concepts, our approach can be seen as a simplified bottomup version of SLGresolution applicable to rangerestricted Datalog programs. Since our approach is also closely related to the alternating fixpoint procedure [27, 28], it can possibly serve as a basis for an integration of the resolutionbased, fixpointbased, and transformationbased ev...
Magic Sets and their Application to Data Integration
 In Proc. International Conference on Database Theory (ICDT 05), Springer LNCS 3363, 2005
, 2005
"... Abstract. We propose a generalization of the wellknown Magic Sets technique to Datalog ¬ programs with (possibly unstratified) negation under stable model semantics. Our technique produces a new program whose evaluation is generally more efficient (due to a smaller instantiation), while preserving ..."
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Cited by 33 (9 self)
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Abstract. We propose a generalization of the wellknown Magic Sets technique to Datalog ¬ programs with (possibly unstratified) negation under stable model semantics. Our technique produces a new program whose evaluation is generally more efficient (due to a smaller instantiation), while preserving soundness under cautious reasoning. Importantly, if the original program is consistent, then full queryequivalence is guaranteed for both brave and cautious reasoning, which turn out to be sound and complete. In order to formally prove the correctness of our Magic Sets transformation, we introduce a novel notion of modularity for Datalog ¬ under the stable model semantics, which is relevant per se. We prove that a module can be evaluated independently from the rest of the program, while preserving soundness under cautious reasoning. For consistent programs, both soundness and completeness are guaranteed for brave reasoning and cautious reasoning as well. Our Magic Sets optimization constitutes an effective method for enhancing the performance of dataintegration systems in which queryanswering is carried out by means of cautious reasoning over Datalog ¬ programs. In fact, preliminary results of experiments in the EU project INFOMIX, show that Magic Sets are fundamental for the scalability of the system. 1
Enhancing the MagicSet Method for Disjunctive Datalog Programs
 In Proc. 20th International Conference on Logic Programming (ICLP 04), Springer LNCS 3132
, 2004
"... Abstract. We present a new technique for the optimization of (partially) bound queries over disjunctive datalog programs. The technique exploits the propagation of query bindings, and extends the MagicSet optimization technique (originally defined for nondisjunctive programs) to the disjunctive ca ..."
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Cited by 33 (10 self)
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Abstract. We present a new technique for the optimization of (partially) bound queries over disjunctive datalog programs. The technique exploits the propagation of query bindings, and extends the MagicSet optimization technique (originally defined for nondisjunctive programs) to the disjunctive case, substantially improving on previously defined approaches. MagicSettransformed disjunctive programs frequently contain redundant rules. We tackle this problem and propose a method for preventing the generation of such superfluous rules during the MagicSet transformation. In addition, we provide an efficient heuristic method for the identification of redundant rules, which can be applied in general, even if MagicSets are not used. We implement all proposed methods in the DLV system – the stateoftheart implementation of disjunctive datalog – and perform some experiments. The experimental results confirm the usefulness of MagicSets for disjunctive datalog, and they highlight the computational gain obtained by our method, which outperforms significantly the previously proposed MagicSet method for disjunctive datalog programs. 1
Partial Stable Models for Logic Programs with Aggregates
 In: LPNMR7. LNCS 2923
, 2004
"... We introduce a family of partial stable model semantics for logic programs with arbitrary aggregate relations. The semantics are parametrized by the interpretation of aggregate relations in threevalued logic. Any semantics in this family satisfies two important properties: (i) it extends the pa ..."
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Cited by 18 (0 self)
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We introduce a family of partial stable model semantics for logic programs with arbitrary aggregate relations. The semantics are parametrized by the interpretation of aggregate relations in threevalued logic. Any semantics in this family satisfies two important properties: (i) it extends the partial stable semantics for normal logic programs and (ii) total stable models are always minimal. We also give a specific instance of the semantics and show that it has several attractive features.
CONTEXTSENSITIVE POINTER ANALYSIS USING BINARY DECISION DIAGRAMS
, 2007
"... in my opinion, it ..."
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Disjunctive ASP with functions: Decidable queries and effective computation. TPLP
, 2010
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A Framework for GoalDirected BottomUp Evaluation of Functional Logic Programs
 In Proc. of FLOPS, LNCS 2024
, 2001
"... Abstract. In this paper we start the design of a functionallogic deductive database language. Given that most logic deductive languages consider bottomup evaluation as operational mechanism, here we will focus on the development of an operational semantics based on bottomup evaluation for function ..."
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Cited by 11 (6 self)
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Abstract. In this paper we start the design of a functionallogic deductive database language. Given that most logic deductive languages consider bottomup evaluation as operational mechanism, here we will focus on the development of an operational semantics based on bottomup evaluation for functional logic languages. As in the logic paradigm, the bottomup evaluation will consist in a magic transformation for a given programquery into a magic programquery for which the bottomup evaluation will simulate the topdown one of the original program. 1
The deductive database system LOLA
 In Proc. 4th Int. Conf. on Logic Programming and Nonmonotonic Reasoning (LPNMR '97), Dagstuhl
, 1997
"... The LOLA system has been designed as the query answering component of a deductive database system and integrates ideas from logic programming and relational query processing. LOLA is based on a clausal logic programming language with function symbols, negation, grouping and aggregation, special pred ..."
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Cited by 10 (6 self)
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The LOLA system has been designed as the query answering component of a deductive database system and integrates ideas from logic programming and relational query processing. LOLA is based on a clausal logic programming language with function symbols, negation, grouping and aggregation, special predicates
Improving the Alternating Fixpoint: The Transformation Approach
, 1997
"... . We present a bottomup algorithm for the computation of the wellfounded model of nondisjunctive logic programs which is based on the set of elementary program transformations studied by Brass and Dix [4, 5]. The transformation approach has been introduced in more detail in [7]. In this paper we ..."
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Cited by 9 (0 self)
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. We present a bottomup algorithm for the computation of the wellfounded model of nondisjunctive logic programs which is based on the set of elementary program transformations studied by Brass and Dix [4, 5]. The transformation approach has been introduced in more detail in [7]. In this paper we present a deeper analysis of its complexity and describe an optimized SCCoriented evaluation. We show that by our method no more work is done than by the alternating fixpoint procedure [23, 24] and that there are examples where our algorithm is significantly superior. 1 Introduction It is likely that the next generation of deductive database systems will support the full class of normal programs and that the wellfounded semantics will be chosen by nearly all system designers, because it has a unique model. Whereas the SLGresolution of Chen and Warren [10, 11, 12] is an elaborate topdown method for the computation of the wellfounded model of a normal program that already led to a full...
DYNAMIC MAGIC SETS FOR DISJUNCTIVE DATALOG PROGRAMS
"... Abstract. Answer set programming (ASP) is a powerful formalism for knowledge representation and common sense reasoning that allows disjunction in rule heads and nonmonotonic negation in bodies. Magic Sets are a technique for optimizing query answering over logic programs and have been originally def ..."
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Abstract. Answer set programming (ASP) is a powerful formalism for knowledge representation and common sense reasoning that allows disjunction in rule heads and nonmonotonic negation in bodies. Magic Sets are a technique for optimizing query answering over logic programs and have been originally defined for standard Datalog, that is, ASP without disjunction and negation. Essentially, the input program is rewritten in order to identify a subset of the program instantiation which is sufficient for answering the query. Dynamic Magic Sets (DMS) are an extension of this technique to ASP. The optimization provided by DMS can be exploited also during the nondeterministic phase of ASP systems. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query (because of these assumptions). This allows for dynamic pruning of the search space, which may result in exponential performance gains. DMS has been implemented in the DLV system and experimental results confirm the effectiveness of the technique.