2,159 research outputs found

    a combined top-down and bottom-up approach

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    The thesis focuses on the interoperability of autonomous legacy databases with the idea of meeting the actual requirements of an organization. The interoperability is resolved by combining the topdown and bottom-up strategies. The legacy objects are extracted from the existing databases through a database reverse engineering process. The business objects are defined by both the organization requirements and the integration of the legacy objects

    Integration of Legacy and Heterogeneous Databases

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    Integrating Distributed Data Over Their Semantic Identity

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    In this paper, we present a method that integrates distributed data managed by a variety of DBMSs. We focus on an infrastructure designed to assist business modelling and requirements analysis. ERA method that describes the enterprise\u27s structure provides metamodels which are stored in the SIS semantic repository. The infrastructure suggested uses the semantics of the database information which are acquired by the application of a database re-engineering method and depicted in a EER model. We explain the framework and we describe the structure of our approach and the mechanisms that accomplish the data integratio

    Technological Spaces: An Initial Appraisal

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    In this paper, we propose a high level view of technological spaces (TS) and relations among these spaces. A technological space is a working context with a set of associated concepts, body of knowledge, tools, required skills, and possibilities. It is often associated to a given user community with shared know-how, educational support, common literature and even workshop and conference regular meetings. Although it is difficult to give a precise definition, some TSs can be easily identified, e.g. the XML TS, the DBMS TS, the abstract syntax TS, the meta-model (OMG/MDA) TS, etc. The purpose of our work is not to define an abstract theory of technological spaces, but to figure out how to work more efficiently by using the best possibilities of each technology. To do so, we need a basic understanding of the similarities and differences between various TSs, and also of the possible operational bridges that will allow transferring the results obtained in one TS to other TS. We hope that the presented industrial vision may help us putting forward the idea that there could be more cooperation than competition among alternative technologies. Furthermore, as the spectrum of such available technologies is rapidly broadening, the necessity to offer clear guidelines when choosing practical solutions to engineering problems is becoming a must, not only for teachers but for project leaders as well

    Reverse Engineering Heterogeneous Applications

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    Nowadays a large majority of software systems are built using various technologies that in turn rely on different languages (e.g. Java, XML, SQL etc.). We call such systems heterogeneous applications (HAs). By contrast, we call software systems that are written in one language homogeneous applications. In HAs the information regarding the structure and the behaviour of the system is spread across various components and languages and the interactions between different application elements could be hidden. In this context applying existing reverse engineering and quality assurance techniques developed for homogeneous applications is not enough. These techniques have been created to measure quality or provide information about one aspect of the system and they cannot grasp the complexity of HAs. In this dissertation we present our approach to support the analysis and evolution of HAs based on: (1) a unified first-class description of HAs and, (2) a meta-model that reifies the concept of horizontal and vertical dependencies between application elements at different levels of abstraction. We implemented our approach in two tools, MooseEE and Carrack. The first is an extension of the Moose platform for software and data analysis and contains our unified meta-model for HAs. The latter is an engine to infer derived dependencies that can support the analysis of associations among the heterogeneous elements composing HA. We validate our approach and tools by case studies on industrial and open-source JEAs which demonstrate how we can handle the complexity of such applications and how we can solve problems deriving from their heterogeneous nature
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