کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
378877 659230 2013 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Data migration: A theoretical perspective
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Data migration: A theoretical perspective
چکیده انگلیسی

In this paper we investigate data migration fundamentals from a theoretical perspective. Following the framework of abstract interpretation, we first discuss models and schemata at different levels of abstraction to establish a Galois connection between abstract and concrete models. A legacy kernel is discovered at a high-level abstraction which consolidates heterogeneous data sources in a legacy system. We then show that migration transformations can be specified via the composition of two subclasses of transformations: property-preserving transformations and property-enhancing transformations. By defining the notions of refinement correctness for property-preserving and property-enhancing transformations, we develop a formal framework for refining transformations occurring in the process of data migration. In order to improve efficiency of static analysis, we further introduce an approach of verifying transformations by approximating abstraction relative to properties of interest, meanwhile preserving the refinement correctness as accurately as possible. The results of this paper lay down a theoretical foundation for developing data migration tools and techniques.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 87, September 2013, Pages 260–278
نویسندگان
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