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Thesis

Model-driven data migration

Abstract:

Information systems often hold data of considerable value. Their continuing development or maintenance will often necessitate evolution of the system and migration of the data from one version to the next: a process that may be expensive, time-consuming, and prone to error. That such a process remains a source of challenges, is recognized by both academia and industry. In current practice, data migration is often considered only in the later stages of development, leaving critical data to be transformed and loaded by hand-written scripts, long after the design process has been completed.

The advent of model-driven engineering offers an opportunity to consider the question of information system evolution and data migration earlier in the development process. A precise account of the proposed changes to an existing system model can be used to predict the consequences for existing data, and to generate the necessary data migration implementation.

This dissertation shows how automatic data migration can be achieved by extending the definition of a data modeling language to include model level operations, each of which corresponds to the addition, modification, or deletion of a model component. Using the Unified Modeling Language (UML) notation as an example, we show how the specification of these operations may be translated into an abstract program in the Abstract Machine Notation (AMN), employed in the B-method, and then formally checked for consistency and applicability prior to translation into a concrete programming notation, such as Structured Query Language (SQL).

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
St Catherine's College
Role:
Author

Contributors

Role:
Supervisor


Publication date:
2012
DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
UUID:
uuid:44ddbf8b-a6a0-4830-baeb-13b2c746802f
Local pid:
ora:12551
Deposit date:
2016-07-19
ARK identifier:

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