Joxan Jaffar, Spiro Michayov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992. 142  Home/Search   Document Not in Database   Summary   Related Articles   Check

....of Tables 1 Ranges for Heart function . 56 2 Executing sequence in the problem of heart funcionality diagnose 59 iv 1 Introduction Constraint Logic Programming (CLP) systems support many different domains such as finite ranges of integers [10, 14] reals [29, 36, 38, 7], finite sets [39, 23] or the Booleans [15, 6] The type of the domain determines the nature of the constraints and the solvers used to solve them. In particular, the cardinalityofthe domain determines the constraint solving procedure so that existing CLP systems have distinct constraint solving ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(!) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....for the length of the tail X in the goal append( H jX ] djejf ] ajbjcjdjejf ] can be found by solving the corresponding abstract goal append(1 X; 3; 6) resulting in X = 2. A possible implementation can be obtained by slightly modifying the CLP (R) 226 R. GIACOBAZZI et al. interpreter in [47] to cope with affine relations. This corresponds to implement (at the meta level) the join operator for affine subspaces so as to combine the computed answer constraints generated by the interpreter. Thus, abstract interpretation for linear size relationships can be joined to a concrete ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339-- 395, 1992.

..... In some applications, may also be satisfaction complete with respect that is, for every c #L, either T = c. The number of instances of CLP(X ) has grown so much in the last years that it would be impractical to cite them all. Classical CLP(X ) systems, so to speak, are CLP(R) JMSY92] which computes over the constraint domain of linear arithmetic over the real numbers, CHIP [DVS 88] which also computes over the domain of Boolean values and functions, and Prolog III [Col87] which has a host of constraint domains. Prolog itself can be seen as CLP(FT ) where is the ....

Joxan Ja#ar, Spiro Michayov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....extension to handle metric constraints. Other researchers have combined logical and constraint reasoning, usually in the context of programming languages. clpr may be thought of as an integration of Prolog and linear programming, and this work introduced the notion of incremental Simplex [ Ja#ar et al. 1992 ] Saraswat s thesis [ Saraswat, 1989 ] formulates a family of programming languages which operate through the incremental construction of a constraint framework. chip [ Van Hentenryck, 1989 ] augments logic programming with the tools to e#ciently solve constraint satisfaction problems (e.g. ....

Joxan Ja#ar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....conflict sets, learning, and backjumping. Other researchers have combined logical and constraint reasoning, usually in the context of programming languages. clpr may be thought of as an integration of Prolog and linear programming, and this work introduced the notion of incremental Simplex [ Ja#ar et al. 1992 ] Saraswat s thesis [ Saraswat, 1989 ] formulates a family of programming languages which operate through the incremental construction of a constraint framework. A variety of recent systems have addressed the issue of integrating metric reasoning into planning. ILPPLAN [ Kautz and Walser, 1999 ....

Joxan Ja#ar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....should be 1, or that two expressions should have the same type. Constraints have been used as a tool to solve many di#erent problems. In each application the domain of the constraints depends on the problem that are being solved. The domains used are as di#erent as the set of real numbers, R [9], an arbitrary finite domain [11, 6] finite terms [17] sets of strings [12] and regular terms [14] It is the latter domain we will look at here. The constraints used in [14] are ine#cient in the sense that there is no known polynomial time algorithm for finding a solution to the constraints ....

Joxan Ja#ar, Spiro Michaylov, Peter J. Stuckey, and Roland H. C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....constraint solver. 1 Introduction The constraint logic programming paradigm [13] generalizes logic programming by replacing the Herbrand universe of terms by other, in general more powerful, domains. Unification of terms is replaced by solving constraints over these domains. For instance, CLP(R) [15, 11] adds real numbers to the Herbrand universe and contains equations and inequations as constraints. The system includes a constraint solver over the real numbers. Since solving nonlinear constraints is a complex problem, the constraint solver in CLP(R) is restricted to linear constraints. Nonlinear ....

....is added. 1 In this simple example the groundness analysis can be improved by considering all constraints in an arbitrary order instead of a left to right order. However, this cannot be done in general if the constraints originate from the execution of several predicates. 2 Similarly to CLP(R) [15] we assume that a CLP(R) program is well typed. 3 In contrast to CLP(R) we do not consider other arithmetic functions like , sin, cos, pow, abs, min and max. These functions can be treated similarly to in our abstract interpretation algorithm. We will discuss this subject in Section 5. 3 ....

[Article contains additional citation context not shown here]

J. Jaffar, S. Michaylov, P.J. Stuckey, and R.H.C. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, Vol. 14, No. 3, pp. 339--395, 1992.

....More resources are needed if larger and more realistic problems are to be used in comparing and contrasting the CLP systems. It should be also noted that we have only compared the FD libraries. Similar comparative studies could also be made for other common domains such as Intervals [2] or Reals [16]. To summarise our results, for maximum efficiency the Ilog SOLVER is best. clp(FD) is also a good candidate provided the size of the problem (measured in number of FD variables) is fairly small. Finally, IF Prolog and SICStus both perform well although, in the tests here, SICStus had the greater ....

JAFFAR J., MICHAYLOV S., STUCKEY P. and YAP R., The CLP(!) language and system. ACM Transactions on Programming languages and Systems, 14(3):339-395, July, 1992.

....the constraint (logic programming) technology. In particular, CHIP [56] was the first CLP language to employ constraint propagation [84] Other examples of CLP related systems are the constraint handling libraries of ILOG [96] and COSYTEC [47] and the CLP languages Prolog III [44, 45] CLP(R) [98], ECLiPSe [95, 179] CIAO [91] and clp(fd) 38] With these systems, many hard application domains have been tackled successfully using constraint related technologies. Examples are circuit verification, scheduling, resource allocation, timetabling, control systems, graphical interfaces, and many ....

J. Jaffar and al. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 1992.

.... the entailment relation is suitably extended to C 0 requiring, for each X; Y; Z 2 Vars: fX ff Y g Y ff X; fX ff Y; Y ff Zg X ff Z; fX; X ff Y g Y: 4 Beware not to confuse CLP(R) the idealized language over the reals [28] with CLP(R) the (far from ideal) implemented language and system [27]. 18 4.2 Bounds and relations analysis for numeric domains The analysis described in [5,6,3] is based on constraint inference, a variant of constraint propagation [18] This technique, developed in the field of artificial intelligence, has been applied to temporal and spatial reasoning [1,38] ....

....agent k n i=1 0 i 0 Theta . To say it operationally, the smash agent globalizes the (local) failure on any of the component domains. This is the only domain independent agent we have. Things become much more interesting when instantiated over particular constraint domains. In the CLP(R) system [27] non linear constraints (like X = Y Z) are delayed (i.e. not treated by the constraint solver) until they become linear (e.g. until either Y or Z are constrained to take a single value) In standard semantic treatments this is modeled in the operational semantics by carrying over, besides the ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....is undefined. Notice that we assume D [ X and its operations encode both the proper X solver and the so called interface between the Herbrand engine and the X solver [8] In particular, the interface is responsible for type checking of the equations it receives. For example in CLP(R) [9] 2 Notice that ff 0 may or may not make the diagram of Figure 1 commute (although often ff 0 turns out to have this property) the interface is responsible for the fact that X = a cannot be consistently added to a constraint store where X was previously classified as numeric. We now turn ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....completeness and uniqueness. Completeness guarantees that for every possible situation, there exists an adaptation action. Uniqueness guarantees that for each situation, there is only one adaptation action which is applicable. To enforce these two properties we use the logic language CLP ( [11]. With this language, we can solve linear arithmetic constraints and perform computations over real numbers (non linear constraints are not allowed) As a consequence, when a condition is expressed as a set of linear constraints, it is possible to verify completeness and uniqueness. Declaration ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....the one hand, constraints are used to restrict the universe of validity of a c term. On the other, inferences that are made out of constraints cause the replacing of subterms in the target term; this is the so called active use of constraints. Similar to the CLP scheme of Jaffar and Lassez (see [JMSY92]) the c calculus give a general scheme for constraint functional programming. The calculus can be instantiated with different constraint languages (possibly over different domains) and we get different calculi for different constraint solvers. It was demonstrated in [CMW93b] that the calculus ....

Joxan Jaffar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(IR) Language and System. ACM Transactions on Programming Languages and Systems, pages 339--395, 1992.

....Figure 1: Explorer allows the user to state constraints, generate designs that satisfy those constraints, and view the generated designs. 3 ParMan ParMan [6] is a collaborative parametric design agent [1, 8, 7] combining the use of agent communication protocols [2] constraint logic programming [3, 4], and a graphical presentation interface. ParMan allows any number of engineers to specify constraints over shared parameters in real time, analyze those constraints locally, export and import constraints to and from other members of the design team, and determine if and how the constraints ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems (TOPLAS), 14(3), 1992.

....a symbolic simplex like solver or boolean unification, instead of traditional resolution. The constraint logic programming scheme of Jaffar and Lassez [JL87] gives a general approach for incorporating constraints in a logic programming language. This has been implemented in the language CLP(IR) JMSY92] which contains a simplex algorithm for solving constraints over the real numbers. In Prolog (see [Mil91] and [MNS87] functional and logic programming are unified using a typed calculus. Logic programs are sets of Harrop formulae which may contain terms. In fact, each formula is a term of ....

....for equals must hold. 5. If t is any closed (i.e. ground) term of the constraint language, then there is a name n such that t = n is provable and this n is unique. This name n will be called the normal form of the closed term t. An example of normal form for constraint languages can be found in [JMSY92] 6. The constraint language must have a notion of free variables and of substitution of free occurrences of variables by terms. 7. The constraint language must satisfy the following property: If C t = n then for every variable x and for every term M C[x : M] t[x : M] n Remark 2.5 In ....

[Article contains additional citation context not shown here]

Joxan Jaffar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(IR) Language and System. ACM Transactions on Programming Languages and Systems, pages 339--395, 1992. 47

....way. For example, a solution for the length of the tail X in the goal append( HjX] djejf ] ajbjcjdjejf] can be found by solving the corresponding abstract goal append(1 X; 3; 6) resulting in X = 2. A possible implementation can be obtained by slightly modifying the CLP (R) interpreter in [47] to cope with affine relations. This corresponds to implement (at the meta level) the join operator for affine subspaces so as to combine the computed answer constraints generated by the interpreter. Thus, abstract interpretation for linear size relationships can be joined to a concrete ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339-- 395, 1992.

....that we do not sacrifice the benefits of a well designed type system just to make type inference easier. This restriction makes type inference more difficult; but if type inference is an optional productivity enhancing tool, our algorithms need not be perfect. Following the designers of CLP(R) [Jaffar et al. 1992], we believe it is better to provide an approximate solution to the type inference problem than to provide a perfect solution to an easier to solve approximation of the type inference problem. We break this rule by excluding F bounded polymorphism and parameterized types only because of the time ....

Joxan Jaffar, Spiro Michaylov, Peter J. Stuckey, and Roland H.C. Yap. The CLP(R) Language and System, ACM Transactions on Programming Languages and Systems, Vol. 14, No. 3, July 1992.

....that attempts to keep it at its current value, so if the variable isn t given a value by some stronger constraint the weakest stay will cause it to remain at its current value. The design of the linear equation cycle solver is adapted from that of the linear equation solver used in CLP(R) [4]. The constraints in the cycle are first converted to linear normal form. If no such form exists, the linear equation cycle solver reports failure to UltraViolet so that another cycle solver could be tried instead. The variables in the cycle are classified as parametric variables, non parametric ....

Joxan Jaffar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....languages: e.g. Eqlog [73] KLEAF [70] Babel [138] etc. An approach to integrating different specification notations in a single language framework is Constraint Logic Programming (CLP) a general language integration mechanism built around Horn clause logic and consistent constraints [86, 87]. The CLP mechanisms enhance Prolog s capabilities for rapid prototyping, mainly because arithmetic, negation, and type recasting are managed in a more elegant way [161] Constraints are also a powerful (declarative) data abstraction mechanism. The CLP paradigm is shortly discussed in Section ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339--394, July 1992.

....and the simple approaches are good enough. Things are much different when this information is required during the analysis. This need arises when dealing with languages which employ some sort of delay mechanism, which are typically based on groundness conditions. One of these languages is CLP(R) [14], where non linear constraints are delayed until they become linear; only then they are sent to the constraint solver. In the context of our work on data flow analysis for CLP(R) we are thus facing the following problem: in programs with many non linear constraints, the abstract interpreter is ....

....all the semantic elegance of concurrent constraint programming languages [18] which provide the basis for their construction. We will now see, staying on an intuitive level and following the approach of [3] for simplicity, examples of how these combinations look like. In the CLP(R) system [14] non linear constraints (like X = Y Z) are delayed (i.e. not treated by the constraint solver) until they become linear (e.g. until either Y or Z are constrained to take a single value) Obviously, this cannot be forgotten in abstract constraint systems intended to formalize correct dataflow ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....vs. efficiency . Thus, the solvers cannot always handle all the constraints the user manipulate in the programming languages. A solver is said to be complete if it is able to solve any constraint defined by the language. However, solvers of CP systems are not always complete: for example CLP(R) [9] does not solve non linear constraints, i.e. they are suspended till they become linear. Although this kind of technique is sufficient for some applications, it is not satisfactory in the general case. Designing a solver that handles all the constraints the programming language provides is a ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 14(3):339-- 395, 1992.

....the class of logic programs whose constraint formulas are drawn from the constraint domain designated by the parameter X. So, for classical logic programming, X would denote the constraint domain consisting of uninterpreted terms 4 and their equality constraints, whereas in the system CLP(R) JMSY92] the constraint domain consists of polynomial inequality constraints over the real numbers. For any constructively decidable constraint domain X, a constraint solver for X can be integrated with a Prolog style top down inference mechanism to obtain an effective interpreter for CLP(X) Before ....

.... the degree of q; CStore.clear( Leaves : chooseruletree(P, q(X1, Xk) let constraint = Solve( project( X1, Xk, AND(CStore.constraints( return (q(X1, Xk) constraint) CLP Algorithm Version 4: Separation of Passive and Active Constraints In systems like CLP(R) JMSY92] the constraint store is divided into two parts, one comprising the (conjunctive) system of active constraints, and the other comprising the system of passive constraints. 4 CLP(R) is based upon a simplex solver for conjunctions of linear inequality constraints. It would therefore appear prima ....

J. Jaffar, S. Michaylov, P. Stuckey, and R.H.C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

....process of constraint solving and the outcome of a computation is a sequence of constraints to which the original query reduces. This powerful idea was embodied since then in many constraint logic programming languages, starting with the CLP(R) language of Jaffar, Michaylov, Stuckey, and Yap [JMSY92] in which linear constraints over reals were allowed, and the CHIP language of Dincbas et al. DVS 88] in which linear constraints over finite domains, combined with constraint propagation, were introduced. A theoretical framework for CHIP was provided in van Hentenryck [Van89] This ....

J. Jaffar, S. Michayov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....are the fundamental control operations on constraints. Again not sufficiently instantiated constraints lead to delays on the outcome of these operations and sometimes lead to incomplete operational semantics. Based on this principle, some well known systems have been developed: CLP(R) [18], CHIP [10, 11] PrologIII [5] AKL [15] An early approach towards CLP has been presented in [32] where a sequential method was utilized. In both LP and Constraint Logic Programming (CLP) control conditions and operations are sensitive to the availability of certain information. In order to ....

J. Jaffar, S. Michaylov, P. J. Stuckey, and R. H. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

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J. Jaffar, S. Michaylov, P. Stuckey and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems 14 (3): 339--395, 1992.

No context found.

J. Jaffar, S. Michaylov, P. Stuckey and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems 14 (3): 339--395, 1992.

No context found.

J. Jaffar, S. Michaylov, P. Stuckey and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems 14 (3): 339--395, 1992.

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JAFFAR J. MICHAYLOV S. STUCKEY P.J. and YAP R.H.C., The CLP(R) Language and System, ACM transactions on Programming Languages and Systems, Vol.14, No.3, July 1992. Pages 339-395.

No context found.

J. Jaffar et al., The CLP(R) Language and System, ACM Transactions on Programming Languages and Systems, Vol.14:3, July 1992, pp 339-395.

No context found.

JAFFAR J. MICHAYLOV S. STUCKEY P.J. and YAP R.H.C., The CLP(R) Language and System, ACM transactions on Programming Languages and Systems, Vol.14, No.3, July 1992. Pages 339-395.

No context found.

Joxan Jaar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339-395, July 1992.

....more e ective. But since we deal with a primitive constraint as a whole the redundant computation created by indexicals will not occur in our approach. 3.1. Constraint Representation The representation we use for our new implementation of a propagation solver is similar to that used in CLP(R) [6] for representing real constraints. Essentially, each primitive constraint is represented as a list of terms appearing in the constraint, plus a constant. Each primitive constraint is tagged with its type (equation, inequality, disequation) and a count of the number of terms appearing in it. Each ....

Joxan Jaar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339-395, July 1992.

....more effective. But since we deal with a primitive constraint as a whole the redundant computation created by indexicals will not occur in our approach. 3. 1 Constraint Representation The representation we use for our new implementation of a propagation solver is similar to that used in CLP(R) [5] for representing real constraints. Essentially, each primitive constraint is represented as a list of terms appearing in the constraint, plus a constant. Each primitive constraint is tagged with its type (equation, inequality, disequation) and a count of the number of terms appearing in it. Each ....

Joxan Jaffar, Spiro Michaylov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....of type overloading, better compile time error checking and generation of more efficient run time code. 1 Introduction Constraint logic programming (CLP) languages are evolving to support more flexible experimentation with constraint solvers. First generation CLP languages, such as CLP(R) [9], provided almost no support. They had a fixed underlying solver for each constraint domain which was viewed as a closed black box. Second generation CLP languages, such as clp(fd) 3] provided more support by viewing the solver as a glass box which the programmer could extend to provide ....

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 4(3):339--395, 1992.

....[19] of Sterling and Kirschenbaum. The use of the Skeletons and Techniques method for developing a significant Prolog application has already been demonstrated [14] In this paper, we investigate using the method to develop significant programs in an arithmetic based CLP language, CLP(R) [9], although we could have used any other arithmetic based CLP language. The application domain will be basic financial modeling. We develop a core set of simple programs that identify the essence of the required computations, and combine these at the source level to develop a complex and powerful ....

....aspects of this problem, and show how they may be used for other applications. These components are as much of an objective as the actual application at hand. The benefit of using CLP(R) for this work comes from a number of quarters: 2 1. As demonstrated by the notorious mortgage program [9], the various programs developed can be at once remarkably simple, flexible and powerful. 2. Even if individual programs use the components with only one calling pattern, different programs can be developed by using the components with different calling patterns. This problem is particularly ....

Joxan Jaffar, Spiro Michaylov, Peter J. Stuckey, and Roland H. C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems (TOPLAS), 14(3):339--395, July 1992.

....logic programming this is frequently called metalogic programming . In this paper, we shall consider meta programming where the object program (the program being manipulated) and the meta program (the program performing the manipulation) are both written in the logic programming language CLP(R) [11]. CLP(R) is a generalization of Prolog that includes real number arithmetic constraints. A principal difference between Prolog and CLP(R) is that equality in CLP(R) is not based solely on the syntactic structure of terms. This has important consequences for metaprogramming, because it means that ....

....of a variable changes. In many systems, such as CLP(R) there is a variety of ways bindings can change, so the trail also needs to contain a tag field that records the type of change so that it may be correctly reversed on backtracking. Various aspects of tagged trailing in CLP(R) are discussed in [11]. The changes to backtracking caused by eval delayed constraints are very simple, since the CLAM already has a tagged value trail. When a binding of a free variable to an eval structure is undone, it is treated essentially like any other binding. The binding of a cell tagged with ETAG is undone ....

Joxan Jaffar, Spiro Michaylov, Peter J. Stuckey, and Roland H. C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

....include other forms of synchronization models for sustain and adding full programmability to the calculus. A prototype implementation is under way. At the heart of this system is a constraint logic program [11] representing a constraint database. The current implementation the CLP(R) system [12], and a superstructure whose main purpose is the management of a collection of reactors. This system is an instance of a larger effort, Open Constraint Programming [13] which discusses a general architecture matching the calculus presented here. The system in particular provides knowledge ....

J. Jaffar, S. Michaylov, P. Stuckey and R. Yap. The CLP(R) Language and System, ACM Transactions on Programming Languages and Systems, 14(3), 1992.

....of uninterpreted functors over real arithmetic terms. A working knowledge of PROLOG programming is assumed in this document; the book by Sterling and Shapiro [20] can serve as a suitable introductory text. Further technical information on CLP(R) is available on language design and implementation [12, 13], metaprogramming [7] and delay mechanisms [14] Additionally, much has been written about applications in electrical engineering [6, 18] differential equations [5, 8] temporal reasoning [1, 2, 3] protocol testing [4] structural analysis and synthesis [15] mechanical engineering [21] user ....

Joxan Jaffar, Spiro Michaylov, Peter J. Stuckey, and Roland H. C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems (TOPLAS), 14(3):339--395, July 1992.

....with core issues, and it can be extended easily to accomodate more complicated database characteristics. A prototype implementation is under way. At the heart of this system is a constraint logic program [5] representing a constraint database. The current implementation uses our own CLP(R) system [6], and a superstructure whose main purpose is the management of a collection of reactors. This system is an instance of a larger effort, Open Constraint Programming [7] which discusses a general architecture matching the calculus presented here. The system in particular provides knowledge ....

J. Jaffar, S. Michaylov, P. Stuckey and R. Yap. The CLP(R) Language and System, ACM Transactions on Programming Languages and Systems, 14(3), July 1992.

No context found.

Joxan Jaffar, Spiro Michayov, Peter Stuckey, and Roland Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992. 142

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J. Jaffar, S. Michaylov, P. J. Stuckey, and R. H. C. Yap. The CLP(R ) language and system. ACM Transactions on Programming Languages and Systems, 14 (3): 339--395, 1992.

No context found.

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(!) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, 1992.

No context found.

Jaffar, J., Michaylov, S., Stuckey, P. &Yap, R. (1992). The CLP(#) language and system. ACM Transactions on Programming Languages and Systems 14(3): 339--395.

No context found.

J. Jaffar, S. Michaylov, P.J. Stuckey, and R.H.C. Yap. The CLP(!) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

No context found.

J. Jaffar, S. Michaylov, P. J. Stuckey, and R. H. C. Yap. The CLP(R ) language and system. ACM Transactions on Programming Languages and Systems, 14 (3): 339--395, 1992.

No context found.

Joxan Ja#ar, Spiro Michaylov, Peter J. Stuckey, and Roland H. C. Yap. The CLP(R) language and system. ACM Transactions on Programming Languages and Systems, 14(3):339--395, July 1992.

No context found.

J. Jaffar, S. Michaylov, P. Stuckey, and R. Yap. The CLP(R) Language and System. ACM Transactions on Programming Languages and Systems, 1991. To appear.

No context found.

Jaffar, et al. The CLP(!) language and system. ACM transactions on programming languages and systems 14, 3 (July 1992), 339-395.

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JAFFAR92 Jaffar, J., Michaylov, S., Stuckey, P., Yap, R. H. C., The CLP() Language and System, ACM Transactions on Programming Languages and Systems, Vol. 14, No. 3, July 1992.

No context found.

JAFFAR92 Jaffar, J., Michaylov, S., Stuckey, P., Yap, R. H. C., The CLP() Language and System, ACM Transactions on Programming Languages and Systems, Vol. 14, No. 3, July 1992.

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