6,125 research outputs found
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MultiView : a methodology for supporting multiple view schemata in object-oriented databases
It has been widely recognized that object-oriented database (OODB) technology needs to be extended to provide a mechanism similar to views in relational database systems. We define an object-oriented view to be an arbitrarily complex virtual schema graph with possibly restructured generalization and decomposition hierarchies - rather than just one virtual class as has been proposed in the literature. In this paper, we propose a methodology, called MultiView, for supporting multiple such view schemata. MultiView breaks the schema design task into the following independent and well-defined subtasks: (1) the customization of type descriptions and object sets of existing classes by deriving virtual classes, (2) the integration of all derived classes into one consistent global schema graph, and (3) the definition of arbitrarily complex view schemata on this augmented global schema. For the first task of MultiView, we define a set of object algebra operators that can be used by the view definer for class customization. For the second task of MultiView, we propose an algorithm that automatically integrates these newly derived virtual classes into the global schema. We solve the third task of MultiView by first letting the view definer explicitly select the desired view classes from the global schema using a view definition language and then by automatically generating a view class hierarchy for these selected classes. In addition, we present algorithms that verify the closure property of a view and, if found to be incomplete, transform it into a closed, yet minimal, view. In this paper, we introduce the fundamental concept of view independence and show MultiView to be view independent. We also outline implementation techniques for realizing MultiView with existing OODB technology
The use of data-mining for the automatic formation of tactics
This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques
Automatic Derivation of Abstract Semantics From Instruction Set Descriptions
Abstracted semantics of instructions of processor-based architectures are an invaluable asset for several formal verification techniques, such as software model checking and static analysis. In the field of model checking, abstract versions of instructions can help counter the state explosion problem, for instance by replacing explicit values by symbolic representations of sets of values. Similar to this, static analyses often operate on an abstract domain in order to reduce complexity, guarantee termination, or both. Hence, for a given microcontroller, the task at hand is to find such abstractions. Due to the large number of available microcontrollers, some of which are even created for specific applications, it is impracticable to rely on human developers to perform this step. Therefore, we propose a technique that starts from imperative descriptions of instructions,
which allows to automate most of the process
ODEDialect: a set of declarative languages for implementing ontology translation systems
Implementing ontology translation systems is a complex task that requires taking many types of translation decisions, which are usually hidden inside their source code. In order to ease building, maintaining and understanding ontology translation systems, we propose ODEDialect, a set of languages to express translation decisions declaratively and at different layers: lexical, syntax, semantics, and pragmatics. This paper describes the three languages that comprise ODEDialect: ODELex, which allows expressing transformations in the lexical layer; ODESyntax, which allows expressing transformations in the syntax layer; and ODESem, which allows expressing transformations in the semantic and pragmatic layers
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Arcadia, a software development environment research project
The research objectives of the Arcadia project are two-fold: discovery and development of environment architecture principles and creation of novel software development tools, particularly powerful analysis tools, which will function within an environment built upon these architectural principles.Work in the architecture area is concerned with providing the framework to support integration while also supporting the often conflicting goal of extensibility. Thus, this area of research is directed toward achieving external integration by providing a consistent, uniform user interface, while still admitting customization and addition of new tools and interface functions. In an effort to also attain internal integration, research is aimed at developing mechanisms for structuring and managing the tools and data objects that populate a software development environment, while facilitating the insertion of new kinds of tools and new classes of objects.The unifying theme of work in the tools area is support for effective analysis at every stage of a software development project. Research is directed toward tools suitable for analyzing pre-implementation descriptions of software, software itself, and towards the production of testing and debugging tools. In many cases, these tools are specifically tailored for applicability to concurrent, distributed, or real-time software systems.The initial focus of Arcadia research is on creating a prototype environment, embodying the architectural principles, which supports Ada1 software development. This prototype environment is itself being developed in Ada.Arcadia is being developed by a consortium of researchers from the University of California at Irvine, the University of Colorado at Boulder, the University of Massachusetts at Amherst, TRW, Incremental Systems Corporation, and The Aerospace Corporation. This paper delineates the research objectives and describes the approaches being taken, the organization of the research endeavor, and current status of the work
Using Ontologies for the Design of Data Warehouses
Obtaining an implementation of a data warehouse is a complex task that forces
designers to acquire wide knowledge of the domain, thus requiring a high level
of expertise and becoming it a prone-to-fail task. Based on our experience, we
have detected a set of situations we have faced up with in real-world projects
in which we believe that the use of ontologies will improve several aspects of
the design of data warehouses. The aim of this article is to describe several
shortcomings of current data warehouse design approaches and discuss the
benefit of using ontologies to overcome them. This work is a starting point for
discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure
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