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[서평]「Applying UML and Patterns - An Introduction to Object-Oriented Analysis and Design」

Integrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, a database may not satisfy those integrity constraints, and for that reason it is said to be inconsistent. However, and most likely, a large portion of the database is still semantically correct, in a sense that has to be made precise. After having provided a formal characterization of consistent data in an inconsistent database, the natural problem emerges of extracting that semantically correct data, as query answers. The consistent data in an inconsistent database is usually characterized as the data that persists across all the database instances that are consistent and minimally differ from the inconsistent instance. Those are the so-called repairs of the database. In particular, the consistent answers to a query posed to the inconsistent database are those answers that can be simultaneously obtained from all the database repairs. As expected, the notion of repair requires an adequate notion of distance that allows for the comparison of databases with respect to how much they differ from the inconsistent instance. On this basis, the minimality condition on repairs can be properly formulated. In this monograph we present and discuss these fundamental concepts, different repair semantics, algorithms for computing consistent answers to queries, and also complexity-theoretic results related to the computation of repairs and doing consistent query answering. Table of Contents: Introduction / The Notions of Repair and Consistent Answer / Tractable CQA and Query Rewriting / Logically Specifying Repairs / Decision Problems in CQA: Complexity and Algorithms / Repairs and Data Cleaning

Database Repairing and Consistent Query Answering

In this paper we describe a distributed object oriented logic programming language in which an object is a collection of threads deductively accessing and updating a shared logic program. The key features of the language, such as static and dynamic object methods and multiple inheritance, are illustrated through a series of small examples. We show how we can implement object servers, allowing remote spawning of objects, which we can use as staging posts for mobile agents. We give as an example an information gathering mobile agent that can be queried about the information it has so far gathered whilst it is gathering new information. Finally we define a class of co-operative reasoning agents that can do resource bounded inference for full first order predicate logic, handling multiple queries and information updates concurrently. We believe that the combination of the concurrent OO and the LP programming paradigms produces a powerful tool for quickly implementing rational multi-agent applications on the internet.

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Computational Logic: Logic Programming and Beyond

Repairing a database means bringing the database in accordance with a given set of integrity constraints by applying some minimal change. If a database can be repaired in more than one way, then the consistent answer to a query is defined as the intersection of the query answers on all repaired versions of the database.Earlier approaches have confined the repair work to deletions and insertions of entire tuples. We propose a theoretical framework that also covers updates as a repair primitive. Update-based repairing is interesting in that it allows rectifying an error within a tuple without deleting the tuple, thereby preserving consistent values in the tuple. Another novel idea is the construct of nucleus: a single database that yields consistent answers to a class of queries, without the need for query rewriting. We show the construction of nuclei for full dependencies and conjunctive queries. Consistent query answering and constructing nuclei is generally intractable under update-based repairing. Nevertheless, we also show some tractable cases of practical interest.

Database repairing using updates

Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational and suitability to application. The paper attempts to expose some of the challenges and prospects for the further development of the field.

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Abduction in Logic Programming

This paper presents a new system, called the A- System, performing abductive reasoning within the framework of Abductive Logic Programming. It is based on a hybrid computational model that implements the abductive search in terms of two tightly coupled processes: a reduction process of the highlevel logical representation to a lower-level constraint store and a lower-level constraint solving process. A set of initial "proof of principle" experiments demonstrate the versatility of the approach stemming from its declarative representation of problems and the good underlying computational behaviour of the system. The approach offers a general methodology of declarative problem solving in AI where an incremental and modular refinement of the high-level representation with extra domain knowledge can improve and scale the computational performance of the framework.

A-system: problem solving through abduction

We introduce an abductive method for a coherent integration of independent datasources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called A system, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to 'recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the 'recovered databases' in terms of the 'preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and - to the best of our knowledge - is more expressive (thus more general) than any other implementation of coherent integration of databases.

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Coherent integration of databases by abductive logic programming

The A-system [4] is a new system for performing abductive reasoning within the framework of Abductive Logic Programming (ALP). The principles behind the system are founded by work on two earlier systems ACLP [2],[3] and SLDNFA(C) [1],[6]. The basic inference mechanism of the system combines abductive logicp rogramming and constraint logicp rogramming. In its computation it reduces the high level specification of the problem and goal at hand to a lower level constraint store. This constraint store is managed by an efficient constraint solver returning information to the abductive reduction process in order to help this in its search for a solution.

A-system: Declarative Programming with Abduction

We introduce a simple and practically efficient method for repairing inconsistent databases. The idea is to properly represent the underlying problem, and then use off-the-shelf applications for efficiently computing the corresponding solutions.

Database Repair by Signed Formulae

We introduce a simple and practical method for repairing inconsistent databases. Given a possibly inconsistent database, the idea is to properly represent the underlying problem, i.e., to describe the possible ways of restoring its consistency. We do so by what we call signed formulae, and show how the `signed theory' that is obtained can be used by a variety of off-the-shelf computational models in order to compute the corresponding solutions, i.e., consistent repairs of the database.

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Bert Van Nuffelen

Papers

A-system: problem solving through abduction

Coherent integration of databases by abductive logic programming

A-system: Declarative Programming with Abduction

Database Repair by Signed Formulae

Computational methods for database repair by signed formulae