This paper shows howalarge class of interprocedural dataflow-analysis problems can be solved precisely in polynomial time. The only restrictions are that the set of dataflowfacts is a finite set, and that the dataflowfunctions distribute overthe confluence operator (either union or intersection). This class of problems includes---but is not limited to---the classical separable problems (also known as "gen/kill" or "bit-vector" problems)---e.g.,reaching definitions, available expressions, and live variables. In addition, the class of problems that our techniques handle includes manynon-separable problems, including trulylive variables, copyconstant propagation, and possibly-uninitialized variables. Anovelaspect of our approach is that an interprocedural dataflow-analysis problem is transformed into a special kind of graph-reachability problem (reachability along interprocedurally realizable paths). The paper presents three polynomial-time algorithms for the realizable-path reachability problem: an exhaustive version, a second exhaustive version that may be more appropriate in the incremental and/or interactive context, and a demand version. The first and third of these algorithms are asymptotically faster than the best previously known realizable-path reachability algorithm. An additional benefit of our techniques is that theylead to improvedalgorithms for twoother kinds of interproceduralanalysis problems: interprocedural flow-sensitive side-effect problems (as studied by Callahan) and interprocedural program slicing (as studied by Horwitz, Reps, and Binkley). CR Categories and Subject Descriptors: D.3.4 [Programming Languages]: Processors - compilers, optimization;E.1 [Data

SLD resolution with negation as finite failure (SLDNF) reflects the procedural interpretation of predicate calculus as a programming language and forms the computational basis for Prolog systems. Despite its advantages for stack-based memory management, SLDNF is often not appropriate for query evaluation for three reasons: a) it may not terminate due to infinite positive recursion; b) it may not terminate due to infinite recursion through negation; c) it may repeatedly evaluate the same literal in a rule body, leading to unacceptable performance. We address three problems fir a goal-oriented query evaluation of general logic programs by presenting tabled evaluation with delaying (SLG resolution).

The evaluation of path expression queries on semistructured data in a distributed asynchronous environment is considered. The focus is on the use of local information expressed in the form of path constraints in the optimization of path expression queries. In particular, decidability and complexity results on the implication problem for path constraints are established.

We consider a bottom-up query-evaluation scheme in which facts of relations are allowed to have nonground terms. The Magic Sets query-rewriting technique is generalized to allow arguments of predicates to be treated as bound even though the rules do not provide ground bindings for those arguments. In particular, we regard as "bound" any argument containing a function symbol or a variable that appears more than once in the argument list. Generalized "magic " predicates are thus defined to compute the set of all goals reached in a top-down exploration of the rules, starting from a given query goal; these goals are not facts of constants as in previous versions of the Magic Sets algorithm. The magic predicates are then used to restrict a bottom-up evaluation of the rules so that there are no redundant actions; that is, every step of the bottom-up computation must be performed by any algorithm that uses the same sideways information passing strategy (sips). The price paid, compared to prev...

Many problems encountered when building applications of database systems involve the manipulation of models. By “model, ” we mean a complex structure that represents a design artifact, such as a relational schema, object-oriented interface, UML model, XML DTD, web-site schema, semantic network, complex document, or software configuration. Many uses of models involve managing changes in models and transformations of data from one model into another. These uses require an explicit representation of “mappings ” between models. We propose to make database systems easier to use for these applications by making “model ” and “model mapping ” first-class objects with special operations that simplify their use. We call this capability model management. In addition to making the case for model management, our main contribution is a sketch of a proposed data model. The data model consists of formal, object-oriented structures for representing models and model mappings, and of high-level algebraic operations on those structures, such as matching, differencing, merging, function application, selection, inversion and instantiation. We focus on structure and semantics, not implementation. 1

This paper describes how a number of program-analysis problems can be solved by transforming them to graph-reachability problems. Some of the program-analysis problems that are amenable to this treatment include program slicing, certain dataflow-analysis problems, and the problem of approximating the possible "shapes" that heap-allocated structures in a program can take on. Relationships between graph reachability and other approaches to program analysis are described. Some techniques that go beyond pure graph reachability are also discussed.

Languages of declarative logic programming differ from other modal nonmonotonic formalisms by lack of syntactic uniformity. For instance, negation as failure can be used in the body of a rule, but not in the head; in disjunctive programs, disjunction is used in the head of a rule, but not in the body; in extended programs, negation as failure can be used on top of classical negation, but not the other way around. We argue that this lack of uniformity should not be viewed as a distinguishing feature of logic programming in general. As a starting point, we take a translation from the language of disjunctive programs with negation as failure and classical negation into MBNF---the logic of minimal belief and negation as failure. A class of theories based on this logic is defined, theories with protected literals, which is syntactically uniform and contains the translations of all programs. We show that theories with protected literals have a semantics similar to the answer set semantics us...

A practical procedure for computing a regular approximation of a logic program is given. Regular approximations are useful in a variety of tasks in debugging, program specialisation and compile-time optimisation. The algorithm shown here incorporates optimisations taken from deductive database fixpoint algorithms and efficient bottom-up abstract interpretation techniques. Frameworks for defining regular approximations have been put forward in the past, but the emphasis has usually been on theoretical aspects. Our results contribute mainly to the development of effective analysis tools that can be applied to large programs. Precision of the approximation can be greatly improved by applying query-answer transformations to a program and a goal, thus capturing some argument dependency information. A novel technique is to use transformations based on computation rules other than left-to-right to improve precision further. We give performance results for our procedure on a range of programs. 1

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The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems.