McMinn, P.S. orcid.org/0000-0001-9137-7433, Wright, C.J., Kinneer, C. et al. (3 more authors) (2017) SchemaAnalyst: Search-Based Test Data Generation for Relational Database Schemas. In: 2016 International Conference on Software Maintenance and Evolution (ICSME). 2016 International Conference on Software Maintenance and Evolution (ICSME 2016), 2/10/2016 - 10/10/2016, Raleigh, North Carolina, USA. IEEE ISBN 978-1-5090-3806-0
Abstract
Data stored in relational databases plays a vital role in many aspects of society. When this data is incorrect, the services that depend on it may be compromised. The database schema is the artefact responsible for maintaining the integrity of stored data. Because of its critical function, the proper testing of the database schema is a task of great importance. Employing a search-based approach to generate high-quality test data for database schemas, SchemaAnalyst is a tool that supports testing this key software component. This presented tool is extensible and includes both an evaluation framework for assessing the quality of the generated tests and full-featured documentation. In addition to describing the design and implementation of SchemaAnalyst and overviewing its efficiency and effectiveness, this paper coincides with the tool’s public release, thereby enhancing practitioners’ ability to test relational database schemas.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper subsequently published in Software Maintenance and Evolution (ICSME), 2016 IEEE International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Sep 2016 08:48 |
Last Modified: | 18 Jul 2017 05:09 |
Published Version: | https://doi.org/10.1109/ICSME.2016.93 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ICSME.2016.93 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104205 |