K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermenegildo, Logic Programming: Proc. North American Conf. 1990.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....the sound removal of the occurcheck [25] optimisation of backtracking [5] the specialisation of unification [27] and the identification [28, 13] and efficient exploitation [23, 14, 24] of independent and parallelism. Early proposals for sharing, freeness and compoundness analyses include [29, 12, 20], 23] and [21] This paper is concerned with a semantic basis for sharing, freeness and compoundness analysis, and in particular, the justification of a high precision abstract unification algorithm. Following the approach of abstract interpretation [10] an abstract unification algorithm (the ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In NACLP'90, pages 531--547. MIT Press, 1990.

.... of sharing analysis are numerous and include: the sound removal of the occur check [22] optimisation of backtracking [3] the specialisation of unification [24] and the elimination of costly checks in independent and parallelism [20, 14, 21] Early proposals for sharing analysis include [25, 10, 19]. This paper is concerned with a semantic basis for sharing analysis, and in particular, the justification of a high precision abstract unification algorithm. Following the approach of abstract interpretation [8] the abstract unification algorithm (the abstract operation) essentially mimics ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In NACLP '90, pages 531--547. MIT Press, 1990.

....be obtained by replacing ask constraints with stronger constraints, which is usually not the case in abstract interpretation. Some solutions to this problem are addressed in [75] Abstract interpretation of (sequential) constraint logic programs was considered firstly by Marriott and Sndergaard [57]. Their treatment is based on abstracting a denotational semantics for constraint logic programs. A meta language based on the typed calculus is used to specify the semantics of logic languages in a denotational style, and both the standard and non standard semantics are viewed as instances of ....

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. In S. K. Debray and M. Hermenegildo, editors, Proc. North American Conference on Logic Programming'90, pages 531--547. The MIT Press, Cambridge, Mass., 1990.

....constraints. Calling context In the next phase, we determine the calling context (in terms of range and endpoint information) for each literal, and replace it by the appropriate propagation method. We assume the reader is somewhat familiar with abstract interpretation of CLP programs (see e.g. [5, 10]) 3.1 Range and Endpoint Descriptions The first phase is a simple bottom up abstract interpretation where we determine which variables must have range domains, and which variables are only involved in endpointrelevant constraints. The bottom up analysis determines for each user defined ....

....so abstract disjunction is defined as Adisj R = Adisj E = #. Projection of descriptions onto a set of variables V is Boolean existential quantification, Aproj R (V, #) Aproj E (V, #) #(V V )#. For recursive programs we can find the least fixpoint in the usual manner (see e.g. [10]) Note that since there are no infinite ascending chains this process is finite. We can alternatively (and this is the approach taken in the implementation) use a constraint based fixpoint rule (as in HindleyMilner type inference, see e.g. 3] which simply ensures that recursive calls have the ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermengildo, editors, Logic Programming: Proceedings of the 1990.

....In the case of logic programs, abstract substitutions typically specify sets of substitutions which describe the call and success patterns of a given clause and abstract unification mimics unifications involving such descriptions. The use of abstract interpretation for CLP has been discussed in [20] by Marriott and Sondergaard. Adapting the framework of [1] for LP to the analysis of CLP is described in [10] Low level optimisations based on abstract interpretation have been discussed by several authors [20, 15, 14] In a recent paper, Marriott and Stuckey [21] discuss three global ....

....such descriptions. The use of abstract interpretation for CLP has been discussed in [20] by Marriott and Sondergaard. Adapting the framework of [1] for LP to the analysis of CLP is described in [10] Low level optimisations based on abstract interpretation have been discussed by several authors [20, 15, 14]. In a recent paper, Marriott and Stuckey [21] discuss three global optimisations: constraint refinement, constraint removal and constraint reordering using a convex hull approximation [9] of the solution space of a system of linear equations and inequalities, and an abstract Fourier algorithm to ....

[Article contains additional citation context not shown here]

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermenegildo, editors, Proceedings of the 1990.

....constraints. Calling context In the next phase, we determine the calling context (in terms of range and endpoint information) for each literal, and replace it by the appropriate propagation method. We assume the reader is somewhat familiar with abstract interpretation of CLP programs (see e.g. [5, 10]) 3.1 Range and Endpoint Descriptions The first phase is a simple bottom up abstract interpretation where we determine which variables must have range domains, and which variables are only involved in endpointrelevant constraints. The bottom up analysis determines for each user defined ....

....so abstract disjunction is defined as Adisj R = Adisj E = #. Projection of descriptions onto a set of variables V is Boolean existential quantification, Aproj R (V, #) Aproj E (V, #) #(V V )#. For recursive programs we can find the least fixpoint in the usual manner (see e.g. [10]) Note that since there are no infinite ascending chains this process is finite. We can alternatively (and this is the approach taken in the implementation) use a constraint based fixpoint rule (as in HindleyMilner type inference, see e.g. 3] which simply ensures that recursive calls have the ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermengildo, editors, Logic Programming: Proceedings of the

....the criteria for safeness. Such verification may employ abstract evaluation of makefile rules, as in abstract interpretation [2] The analysis framework comprises a semantic definition for make which is in some ways similar to the semantic defi nition for (constraint) logic programs given in [6]. Makefile execution bears resemblence with logic program execution (as defined in, e.g. 5] Makefile execution is query driven, and does not assign values to global variables. This similarity with logic programs also motivates the use of the notions of satisfiability of makefile rules and ....

.... R [ T : Ds; C] #V, Cs, S# = let #V # , Cs # , S # # = # (T [ M ] Ds #V, Cs, S# in if S # = T : Ds; C) then #V # , Cs # , S # # else #V # , Cs # ; C) exec C S # # The definition of M is in some ways similar to the semantic definition for constraint logic programs given in [6], due to the similarity between the reduction of a list of goals in constraint logic program exectution, vs. make s reduction of a list of targets. In the sequel we build on the graph based as well as the formal semantic definition. 8. DERIVABILITY The goal in the remainder of the paper is to ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs, Proc. North American Conference on Logic Programming, Austin, 1988, pages 521-540.

....1992; Van Roy and Despain 1992; Warren et al. 1988] Thus, it is natural to expect that this technique should also be useful in the context of CLP. A few general frameworks have already been defined for this purpose [Bruynooghe and Janssens 1992; Codognet and Fil e 1992; Giacobazzi et al. 1993; Marriott and Sndergaard 1990]. However, one common characteristic of these frameworks is that they are either not implementation oriented or depart from the approaches that have been so far quite successful in the analysis of traditional logic programming (LP) languages. This article shows how some of the LP based techniques ....

Marriott, K. and Sndergaard, H. 1990. Analysis of constraint logic programs. In Proceedings of the 1990 North American Conference on Logic Programming, S. Debray and M. Hermenegildo, Eds. MIT Press, Cambridge, Mass., 531--547.

....for the abstract interpretation of logic programs [3] since the operational semantics of CLP(R) is very similar to logic programming. The only difference is the use of sets of constraints instead of substitutions. Therefore any other framework may also be applicable. Marriott and Sndergaard [19] have developed a particular framework for the abstract interpretation of constraint logic programming languages based on a denotational description of the semantics. They have also shown the application of their framework to the freeness and groundness analysis of CLP programs. However, they have ....

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. In Proc. of the 1990 North American Conference on Logic Programming, pp. 531-- 547. MIT Press, 1990.

....has been studied later by Cortesi and File in [17] They also introduced the domain Sharing# that is aimed at capturing all the information of ASub and Sharing. In reality, Sharing# is more precise than the reduced product [25] of ASub and Sharing, as Sharing# contains the domain Prop [19,49] (or Pos, as it is now less ambiguously called [1] for the propagation of groundness information. Codish et al. propose a more pragmatic way of integrating the information of ASub and Sharing [15] performing the analysis with both the domains at the same time, and exchanging information between ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. K. Debray and M. Hermenegildo, editors, Logic Programming: Proceedings of the North American Conference, MIT Press Series in Logic Programming, pages 531--547, Austin, Texas, USA, 1990. The MIT Press.

.... of sharing analysis are numerous and include: the sound removal of the occur check [22] optimisation of backtracking [3] the specialisation of unification [24] and the elimination of costly checks in independent and parallelism [20, 14, 21] Early proposals for sharing analysis include [25, 10, 19]. This paper is concerned with a semantic basis for sharing analysis, and in particular, the justification of a high precision abstract unification algorithm. Following the approach of abstract interpretation [8] the abstract unification algorithm (the abstract operation) essentially mimics ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In NACLP '90, pages 531--547. MIT Press, 1990.

....has been studied later by Cortesi and Fil e in [17] They also introduced the domain Sharing that is aimed at capturing all the information of ASub and Sharing. In reality, Sharing is more precise than the reduced product [25] of ASub and Sharing, as Sharing contains the domain Prop [19,49] (or Pos, as it is now less ambiguously called [1] for the propagation of groundness information. Codish et al. propose a more pragmatic way of integrating the information of ASub and Sharing [15] performing the analysis with both the domains at the same time, and exchanging information between ....

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. K. Debray and M. Hermenegildo, editors, Logic Programming: Proceedings of the North American Conference, MIT Press Series in Logic Programming, pages 531-547, Austin, Texas, USA, 1990. The MIT Press.

.... Suitable 2 abstract versions of the immediate consequence operators that we will introduce can be used for bottom up abstract interpretation (i.e. fixpoint computation of the abstract model) Abstract interpretation of CLP programs has been considered in a denotational semantics framework in [38], while we can generalize the bottom up approach in [3] More interestingly, the compositional semantics can be used to develop a framework for the modular analysis of CLP programs. This is particularly relevant for practical applications where modularity can help to reduce the size and the ....

....be used for some applications that we briefly discuss below. Program analysis. The answer constraint semantics F 3 can be used to develop semantics based tools for the analysis of CLP programs. Abstract interpretation of CLP programs has been considered in a denotational semantics framework in [38], while by using suitable abstract versions of the immediate consequence operators T 3 P we can generalize the bottom up approach in [3] The compositional semantics in [7] has been used in [10] to develop a modular analysis for pure logic programs. Analogously, our F Omega semantics and its ....

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. In S. K. Debray and M. Hermenegildo, editors, Proc. North American Conf. on Logic Programming, pages 531--547. The MIT Press, Cambridge, Mass., 1990.

....be obtained by replacing ask constraints with stronger constraints, which is usually not the case in abstract interpretation. Some solutions to this problem are addressed in [75] Abstract interpretation of (sequential) constraint logic programs was considered firstly by Marriott and Sndergaard [57]. Their treatment is based on abstracting a denotational semantics for constraint logic programs. A meta language based on the typed calculus is used to specify the semantics of logic languages in a denotational style, and both the standard and non standard semantics are viewed as instances of ....

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. In S. K. Debray and M. Hermenegildo, editors, Proc. North American Conference on Logic Programming'90, pages 531--547. The MIT Press, Cambridge, Mass., 1990.

....In contrast, differences in the fixed point components are relatively minor, and it is possible to speak of an idealized generic algorithm or engine that encompasses the essence of the fixed point computation. Some specific descriptions of engines are [9] for logic programs, and more recently, [10], for constraint logic programs. In earlier work [6] a new engine, called the unfolding engine, was presented for the analysis of logic programs. Its main advantage was improved accuracy over the standard engine, regardless of the abstract domain used. A fundamental difference between the ....

....these algorithms, and is at least as accurate as any of them. We call this idealized engine the standard engine, and it can be argued that this algorithm is the most obvious embodiment of an abstract domain into an analyzer. More detailed formalizations of this engine can be obtained from [10] and [2] In general, each analysis algorithm starts by associating a value from the chosen abstract domain D with designated parts of the program. The operation of the algorithm then consists of repeatedly recomputing each value from the values previously computed. In what follows, we give, for ....

K. Marriott and H. Sndergaard, "Analysis of Constraint Logic Programs", Proc. 1990 North American Conf. on Logic Programming, 531-547, 1990.

....a large literature on transformation operations is the area of Constraint Logic Programs (CLP) For this paradigm, the literature on transformations can be divided into two main branches. On one hand we nd methods which focus exclusively on the manipulation of the constraint for compile time [18, 19] and for low level local optimization [15] On the other hand there are techniques such as the unfold fold transformation systems, which were developed initially for Logic Programs [28] and then applied to CLP [16, 1, 8] and to ccp in [9] These ones focus primarily on the declarative side of the ....

Kim Marriott and Harald Sndergaard. Analysis of constraint logic programs. In Saumya Debray and Manuel Hermenegildo, editors, Proceedings North American Conference on Logic Programming. MIT Press, 1990.

....The main conceptual contribution of the paper is to show that sophisticated static analyses and source to source transformations can produce dramatic (often asymptotic) speedups for CLP( Lin ) programs. Much research has been devoted to abstract interpretation of CLP( Lin ) e.g. [6, 7, 14, 16, 19]) but almost no experimental results have appeared to quantify the possible benefits. The only exception we are aware of is the system described in [10] but no reordering or constraint removal is performed in the system. As we show in this paper, reordering is probably the most fundamental ....

....One ig g It contains of course the query but also many other abstract stores which characterize constraint store occurring at runtime as input to mg. For instance, the second abstract store captures the stores encountered for the first recursive call to mg. 4. 3 The Domain Prop The domain Prop [14, 20] is an effective domain to compute groundness information for Prolog. It can be extended easily to infer fixed variables in CLP (e.g. 7] Its key idea is to represent the information through a Boolean formula. Informally speaking, a formula x y means that, whenever x is fixed, y is fixed and ....

K. Marriott and H. Sondergaard. Analysis of Constraint Logic Programs. In Proceedings of the North American Conference on Logic Programming (NACLP-90), Austin, TX, October 1990.

....Implementation and Evaluation of the Domain Prop Baudouin Le Charlier University of Namur, 21 rue Grandgagnage, B 5000 Namur (Belgium) Email: ble info.fundp.ac. be Pascal Van Hentenryck Brown University, Box 1910, Providence, RI 02912 (USA) Email: pvh cs.brown.edu Abstract The domain Prop [22, 8] is a conceptually simple and elegant abstract domain to compute groundness information for Prolog programs. In particular, abstract substitutions are represented by Boolean functions built using the logical connectives , Prop has raised much theoretical interest recently but little is known ....

.... (e.g. 1, 3, 2, 7, 20, 21, 23, 30] the algorithms (e.g. 2, 6, 15, 16, 26] the abstract domains (e.g. 4, 14, 25] and the implementations (e.g. 13, 18, 12, 29] An abstract domain which has raised much interest in recent years is the domain Prop proposed by Marriott and Sondergaard [22]. The domain is intended to compute groundness information in Prolog programs. It is conceptually simple and elegant since abstract substitutions are represented by Boolean functions built using the logical connectives , The domain has been further investigated in [8] and related to other ....

K. Marriott and H. Sondergaard. Analysis of Constraint Logic Programs. In Proceedings of the North-American Conference on Logic Programming (NACLP-90), Austin, Tx, October 1990.

....In contrast, differences in the fixed point components are relatively minor, and it is possible to speak of an idealized generic algorithm or engine that encompasses the essence of the fixed point computation. Some specific descriptions of engines are [9] for logic programs, and more recently, [10], for constraint logic programs. In earlier work [6] a new engine, called the unfolding engine, was presented for the analysis of logic programs. Its main advantage was improved accuracy over the standard engine, regardless of the abstract domain used. A fundamental difference between the ....

K. Marriott and H. Søndergaard, "Analysis of Constraint Logic Programs", Proc. 1990 North American Conf. on Logic Programming, 531-547, 1990.

No context found.

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermenegildo, Logic Programming: Proc. North American Conf. 1990.

No context found.

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermenegildo, Logic Programming: Proc. North American Conf. 1990.

No context found.

K. Marriott and H. Sndergaard. Analysis of constraint logic programs. In S. Debray and M. Hermenegildo, Logic Programming: Proc. North American Conf. 1990, pages 531--547. MIT Press, 1990.

.... and intra procedural analysis) that is, program information (descriptions) is inferred about the calls between different rules of the program (as well as inferring the local information within each rule) The global analysis is based on abstract interpretation of constraint logic programs [Marriott and Sndergaard 1990; Garc ia de la Banda et al. 1996] in which operations in the execution of the goal are mimicked by abstract operations on the domain of descriptions (the analyses) Conceptually, the analyzer takes a program and goal and annotates each point in the program with an approximate description of the ....

Marriott, K. and Sndergaard, H. 1990. Analysis of constraint logic programs. In Logic Programming: Proceedings of the North American Conference 1990, S. Debray and M. Hermenegildo, Eds. MIT Press, Cambridge, Mass., 531--547.

....the interface, and the code for variable lookup, order of evaluation and assignment or testing could be hardwired in. In this section we sketch how a variant of mode analysis [4, 12] used in Prolog compilation can be used to provide such information to the compiler. The reader is referred to [11] for a formal framework in which to express this analysis. A mode analysis finds call patterns to describe the form of runtime calls to predicates. In a simple Prolog mode analysis the call pattern for an n argument predicate p is of the form p(d 1 ; d n ) where d i 2 fGnd ; Var ; ....

....of C . Given that a constraint is future redundant in a clause in the context of all of the clause s calling constraints, we can safely apply the future redundancy optimization. To prove future redundancy in the context of all calling constraints, we can use abstract interpretation techniques [11]. These can find descriptions of the inequalities that always hold between the variables in the clause head whenever the clause is called. A simple domain for this purpose is the set of constraints which are conjunctions of strict and non strict inequalities between variables and the constants 0, ....

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. Proc. of the 1990 North American Conference on Logic Programming, 521--540, 1990.

No context found.

K. Marriott and H. Sndergaard. Analysis of Constraint Logic Programs. In S. Debray and M. Hermenegildo, editors, Proc. North American Conf. on Logic Programming'90, pages 531-- 547. The MIT Press, Cambridge, Mass., 1990.

First 50 documents

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC