A logical framework for querying and repairing inconsistent databases

In this paper, we address the problem of managing inconsistent databases, i.e., databases violating integrity constraints. We propose a general logic framework for computing repairs and consistent answers over inconsistent databases. A repair for a possibly inconsistent database is a minimal set of insert and delete operations which makes the database consistent, whereas a consistent answer is a set of tuples derived from the database, satisfying all integrity constraints. In our framework, different types of rules defining general integrity constraints, repair constraints (i.e., rules defining conditions on the insertion or deletion of atoms), and prioritized constraints (i.e., rules defining priorities among updates and repairs) are considered. We propose a technique based on the rewriting of constraints into (prioritized) extended disjunctive rules with two different forms of negation (negation as failure and classical negation). The disjunctive program can be used for two different purposes: to compute "repairs" for the database and produce consistent answers, i.e., a maximal set of atoms which do not violate the constraints. We show that our technique is sound, complete (each preferred stable model defines a repair and each repair is derived from a preferred stable model), and more general than techniques previously proposed.     

A general framework for debugging

The state of the art of debugging is examined. A debugged process model that serves as the basis of a general debugging framework is described. The relationship of the model to traditional debugging processes and support tools is discussed. A minimal set of requirements for a general debugging framework is described in terms of both the theory behind debugging methodologies and the support tools. An execution monitor, Eden, that serves as a debugging tool within this general framework is described     

A general framework for architecture composability

Architectures depict design principles: paradigms that can be understood by all, allow thinking on a higher plane and avoiding low-level mistakes. They provide means for ensuring correctness by construction by enforcing global properties characterizing the coordination between components. An architecture can be considered as an operator A that, applied to a set of components \({\mathcal{B}}\), builds a composite component \({A(\mathcal{B})}\) meeting a characteristic property \({\Phi}\). Architecture composability is a basic and common problem faced by system designers. In this paper, we propose a formal and general framework for architecture composability based on an associative, commutative and idempotent architecture composition operator \({\oplus}\). The main result is that if two architectures A ₁ and A ₂ enforce respectively safety properties \({\Phi_{1}}\) and \({\Phi_{2}}\), the architecture \({A_{1} \oplus A_{2}}\) enforces the property \({\Phi_{1} \land \Phi_{2}}\), that is both properties are preserved by architecture composition. We also establish preservation of liveness properties by architecture composition. The presented results are illustrated by a running example and a case study.     

A general framework for reason maintenance

There are several different kinds of reason-maintenance system in existence, which provide rather different functionalities. I present a general structure that subsumes most such systems, and that allows some new behaviors to emerge. The general framework is based on logic-style clauses (disjunctions of literals) instead of justifications. Literals are tagged with labels that say what assumption sets make them true and false. Nonmonotonicity is implemented by allowing clauses to contain disjuncts of the form Lp, which supports propagation through a clause whenever p is not known to be true. The resulting system supports two popular styles of dependency-directed backtracking, using nogoods and assumption retraction. Assumption retraction does not require a separate contradiction-elimination phase, but occurs automatically during label propagation. Label propagation can be achieved by the usual variants of Boolean constraint propagation, provided there are no “odd loops” through the clauses, and it can be shown that the system itself never creates odd loops.     

A self-stabilizing algorithm for constructing weakly connected minimal dominating sets

This paper presents a new distributed self-stabilizing algorithm for the weakly connected minimal dominating set problem. It assumes a self-stabilizing algorithm to compute a breadth-first tree. Using an unfair distributed scheduler the algorithm stabilizes in at most O(nmA) moves, where A is the number of moves to construct a breadth-first tree. All previously known algorithms required an exponential number of moves.     

A general framework for relation graph clustering

Relation graphs, in which multi-type (or single type) nodes are related to each other, frequently arise in many important applications, such as Web mining, information retrieval, bioinformatics, and epidemiology. In this study, We propose a general framework for clustering on relation graphs. Under this framework, we derive a family of clustering algorithms including both hard and soft versions, which are capable of learning cluster patterns from relation graphs with various structures and statistical properties. A number of classic approaches on special cases of relation graphs, such as traditional graphs with singly-type nodes and bi-type relation graphs with two types of nodes, can be viewed as special cases of the proposed framework. The theoretic analysis and experiments demonstrate the great potential and effectiveness of the proposed framework and algorithm.     

A general framework for reasoning about change

The capability to represent and use concepts like time and events in computer science is essential to solve a wide class of problems characterized by the notion of change. Real-time, databases and multimedia are just a few of several areas which needs good tools to deal with time. Another area where this concepts are essential is artificial intelligence because an agent must be able to reason about a dynamic environment. In this work a formalism is proposed which allows the representation and use of several features that had been recognized as useful in the attempts to solve such class of problems. A general framework based on a many-sorted logic is proposed centering our attention in issues such as the representation of time, actions, properties, events and causality. The proposal is compared with related work from the temporal logic and artificial intelligence areas. This work complements and enhances previously related efforts on formalizing temporal concepts with the same purpose. Juan Carlos Augusto, Ph.D.: He is a Lecturer in the Department of Computer Science at Universidad Nacional del Sur (Argentina), where he graduated as Licenciado en Ciencias de la Computacion and Doctor en Ciencias de la Computacion. Currently on leave in the Department of Electronics and Computer Science, University of Southampton (United Kingdom). His research interests are focused in the dynamic aspects of computing systems. This involves solving conceptual problems related to the specification of time and change and designing tools to improve systems in several areas of computer science, such as artificial intelligence, databases, multimedia, software verification and real-time systems. He has been conducting research on temporal representation and reasoning since 1993. Throughout these years he had the opportunity to contribute to several research projects as a researcher and has head or co-head of research groups. Other activities and contributions to highlight are the organization of international events, editorial work and supervision of postgraduate students, all of which contributes to the generation and dissemination of knowledge about the dynamic aspects of computing systems.     

A general framework for computing block accesses

A physcial database system design should take account of skewed block access distributions, nonuniformly distributed attribute domains, and dependent attributes. In this paper we drive general formulas for the number of blocks accessed under these assumptions by considering a class of related occupancy problems. We then proceed to develop robust and accurate approximations for these formulas. We investigate three classes of approximation methods, respectively based on generating functions, Taylor series expansions, and majorization. These approximations are simple to use and more accurate than the cost estimate formulas generated by making uniformity and independence assumptions. Thus they are more representative of the actual database environment, and can be utilized by a query optimizer for better performance.     

A general framework for coherence in a CKBS

Coherence in a distributed system is meant to offset the disadvantages of distribution. The paper explores four issues under coherence, namely preservation of knowledge consistency across the agents, reliability of the overall system, integration of local solutions and the global performance. It presents some general strategies that can be employed to improve coherence in a CKBS, which include a weak consistency with versions for knowledge revision, and a recovery mechanism based on a hierarchic three-stage coordination, which ensures the correct isolation of potentially hierarchic multiagent actions. The paper goes on to identify the sources and classes of conflicts in global integration, and it suggests remedies, which at worst case would involve negotiation. In global performance, it focusses on planning and result synthesis, as the two most important problem domains, and suggests strategies ameliorate performance.     

A general framework for types in graph rewriting

We investigate a general framework which can be instantiated in order to obtain type systems for graph rewriting, allowing us to statically infer behavioural properties of a graph. We describe conditions such as the subject reduction property and compositionality that should be satisfied by such a framework. We present a methodology for proving these conditions, specifically we prove that it is sufficient to show properties that are local to graph transformation rules. In order to show the applicability of this framework, we describe in several case studies how to integrate existing type systems (for the π-calculus and the λ-calculus) and a system for typing acyclic graphs. This is a completely revised and extended version of a paper of which an earlier version has appeared in FSTTCS '00.     

A general shape context framework for object identification

A general shape context framework is proposed for object/image retrieval in occluded and cluttered environment with hundreds of models as the potential matches of an input. The approach is general since it does not require separation of input objects from complex background. It works by first extracting consistent and structurally unique local neighborhood information from inputs or models, and then voting on the optimal matches. Its performance degrades gracefully with respect to the amount of structural information that is being occluded or lost. The local neighborhood information applicable to the system can be shape, color, texture feature, etc. Currently, we employ shape information only. The mechanism of voting is based on a novel hyper cube based indexing structure, and driven by dynamic programming. The proposed concepts have been tested on database with thousands of images. Very encouraging results have been obtained.     

A general framework for scalable transductive transfer learning

Transductive transfer learning is one special type of transfer learning problem, in which abundant labeled examples are available in the source domain and only unlabeled examples are available in the target domain. It easily finds applications in spam filtering, microblogging mining, and so on. In this paper, we propose a general framework to solve the problem by mapping the input features in both the source domain and the target domain into a shared latent space and simultaneously minimizing the feature reconstruction loss and prediction loss. We develop one specific example of the framework, namely latent large-margin transductive transfer learning algorithm, and analyze its theoretic bound of classification loss via Rademacher complexity. We also provide a unified view of several popular transfer learning algorithms under our framework. Experiment results on one synthetic dataset and three application datasets demonstrate the advantages of the proposed algorithm over the other state-of-the-art ones.     

A general framework for 3D model co-alignment

3D model alignment is a fundamental step in many shape analysis processes, and various algorithms have been proposed to solve this problem. However, to the best of our knowledge, they are effective only on specific categories of models. Therefore, we present a novel framework that can align general categories by combining different features together. In order to align given groups of models, multiple features are evaluated first in this framework, according to three types of quantified characteristics, i.e., the intensity, the uniqueness and the consistency. Then, the quantified characteristics are combined into scores and a data-driven model is learned to predict the alignment errors according to the scores. Finally, the features with the minimum predicted alignment errors are selected to align the given groups. Experimental results show that our framework can generate consistent alignments on general categories, which are much better than those generated using single features.     

A general framework for time-aware decision support systems

In this paper we present a general framework for time-aware decision support systems. The framework uses the state-of-the-art tOWL language for the representation of temporal knowledge and enables temporal reasoning over the information that is represented in a knowledge base. Our approach uses state-of-the-art Semantic Web technology for handling temporal data. Through such an approach, the designer of a system can focus on the application intelligence rather than enforcing/checking data related restrictions manually. Also, there is an increased support for reuse of temporal reasoning tools across applications. We illustrate the applicability of our framework by building a market recommendations aggregation system. This system automatically collects market recommendations from online sources and, based on the past performance of the analysts that issued a recommendation, generates an aggregated recommendation in the form of a buy, hold, or sell advice. We illustrate the flexibility of our proposed system by implementing multiple methods for the aggregation of market recommendations.     

A general compiler framework for speculative multithreaded processors

Speculative multithreading (SpMT) promises to be an effective mechanism for parallelizing nonnumeric programs, which tend to have irregular and pointer-intensive data structures and complex flows of control. Proper thread formation is crucial for obtaining good speedup in an SpMT system. This paper presents a compiler framework for partitioning a sequential program into multiple threads for parallel execution in an SpMT system. This framework is very general and supports speculative threads, nonspeculative threads, loop-centric threads, and out-of-order thread spawning. It is therefore useful for compiling for a wide variety of SpMT architectures. For effective partitioning of programs, the compiler uses profiling, interprocedural pointer analysis, data dependence information, and control dependence information. The compiler is implemented on the SUIF-MachSUIF platform. A simulation-based evaluation of the generated threads shows that the use of nonspeculative threads and nonloop speculative threads provides a significant increase in speedup for nonnumeric programs.     

A Web-Service based framework for analyzing and measuring business performance

The web services paradigm provides organizations with an environment to enhance B2B communications. The aim is to create modularized services supporting the business processes within their organization and also those external entities participating in these same business processes. Current web service frameworks do not include the functionality required for web service execution performance measurement from an organization perspective. As such, a shift to this paradigm is at the expense of the organizations performance knowledge, as this knowledge will become buried within the internal processing of the web service platform. This research introduces an approach to reclaim and improve this knowledge for the organization establishing a framework that enables the definition of web services from a performance measurement perspective, together with the logging and analysis of the enactment of web services. This framework utilizes web service concepts, DSS principles, and agent technologies, to enable feedback on the organizations performance measures through the analysis of the web services. A key benefit of this work is that the data is stored once but provides information both to the customer and the supplier of a web service, removing the need for development of internal web service performance monitoring.     

A general minimal residual Krylov subspace method for large-scalemodel reduction

This paper considers approximating a given nth-order stable transfer matrix G(s) by an rth-order stable transfer matrix G_r(s) in which n≫r, and where n is large. The Arnoldi process is used to generate a basis to a part of the controllability subspace associated with the realization of G(s), and a residual error is defined for any approximation in this subspace. We establish that minimizing the L_∞ norm of this residual error over the set of stable approximations leads to a 2-block distance problem. Finally, the solution of this distance problem is used to construct reduced-order approximate models. The behavior of the algorithms is illustrated with a simple example