Islam, Mohammad Mahmudul (2025) Reverse engineering for the subsequent creation of relational models. Masters thesis, Universität Rostock.
Full text not available from this repository.Abstract
Data’s massive production has changed how we live, work and collaborate. As accessing large databases becomes increasingly affordable and widely available, numerous data-intensive applications have emerged in various fields, including scientific research, healthcare, sports, industry, and many more. However, many datasets are poorly structured and designed, often containing missing, non-existent, or incorrect documentation, and lacking essential design information. When this type of data is required for modern research, whether for statistical analysis or artificial intelligence, it is crucial first to understand its structure, which can be both challenging and time-consuming. Furthermore, identifying relationships between tables and columns requires significant time and effort. Manual processing not only increases the chances of errors but also adds to the costs. Nevertheless, if we can identify key relational properties and data dependencies from a dataset, it is possible to generate a relational model by combining these properties. To solve this problem, we will design and develop a system that automates the identification of important relational properties and the generation of a complete relational model from existing data. Our research will focus on exploring various methods and techniques of database reverse engineering, relational models, and data dependencies. By combining these methods, we aim to create a web-based application that accepts a database as input and generates both key relational properties and a complete relational model as output. In addition, we are developing a user-friendly interface to use the system for data analysis and optimization. To evaluate the effectiveness and accuracy of our application, we will conduct tests with different databases and compare the results. Overall, our study will provide a systematic approach to the reverse engineering of relational databases and the automation of the extraction of key relational properties and data dependencies. Our system will help users to understand the structure of their databases. In this study, the system will support MySQL and PostgreSQL databases. In the future, further research will be conducted to expand the system’s capabilities to support other types of databases and different dataset formats.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Autorenart > Studentische Arbeiten > Masterarbeit Forschungsthemen > Schemaextraktion Autorenart > Studentische Arbeiten |
| Depositing User: | Dbis Admin |
| Date Deposited: | 01 Jul 2025 07:57 |
| Last Modified: | 01 Jul 2025 07:57 |
| URI: | https://eprints.dbis.informatik.uni-rostock.de/id/eprint/1129 |
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