Relational-Object Mapping of Databases.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Relational-Object Mapping of Databases.
Συγγραφείς: Tonis, Radu Bucea Manea1 radumanea@univ-danubius.ro
Πηγή: EIRP Proceedings. 2024, Vol. 19 Issue 1, p524-530. 7p.
Θεματικοί όροι: *Object-oriented programming languages, *Relational databases, *Databases, *Programming languages, Scientific method
Περίληψη: Mapping relational databases is a programming technique that enables developers to interact with the database using objects, which are instances of classes defined in a specific programming language. Objectives: This paper propose a scientific method based on several rules in order to transform the logic layer of a relational database into an object model formalized in a class diagram. Prior Work: This research is based on C.J. Date logic and relational approach on modelling relational databases. Approach: We are using the high-level Microsoft C# object-oriented programming language in order to implement the object model of a classic transactional database employing a set of rules and a specific library for serializing collections of objects for a dedicated (MongoDB) persistence layer, Results: the JSON serialized form of the objects is further used to generate new instances according to the business application layer. Implications: The back & forward transformations without information loss by serializing and deserializing objects according to a predefined data scheme validates the methodology proposed by this paper. Value: The importance of our research resides in the plenitude of source code utilized for exemplifying our methodology and the diversity of real-life situations that might benefit of our research in terms of efficiency and consistent data management. [ABSTRACT FROM AUTHOR]
Copyright of EIRP Proceedings is the property of Danubius University of Galati and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Relational-Object Mapping of Databases.
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– Name: Abstract
  Label: Abstract
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  Data: Mapping relational databases is a programming technique that enables developers to interact with the database using objects, which are instances of classes defined in a specific programming language. Objectives: This paper propose a scientific method based on several rules in order to transform the logic layer of a relational database into an object model formalized in a class diagram. Prior Work: This research is based on C.J. Date logic and relational approach on modelling relational databases. Approach: We are using the high-level Microsoft C# object-oriented programming language in order to implement the object model of a classic transactional database employing a set of rules and a specific library for serializing collections of objects for a dedicated (MongoDB) persistence layer, Results: the JSON serialized form of the objects is further used to generate new instances according to the business application layer. Implications: The back & forward transformations without information loss by serializing and deserializing objects according to a predefined data scheme validates the methodology proposed by this paper. Value: The importance of our research resides in the plenitude of source code utilized for exemplifying our methodology and the diversity of real-life situations that might benefit of our research in terms of efficiency and consistent data management. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of EIRP Proceedings is the property of Danubius University of Galati and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Relational databases
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