Paige, Richard F. orcid.org/0000-0002-1978-9852 (2018) Engineering bidirectional transformations. In: Gibbons, Jeremy and Stevens, Perdita, (eds.) Bidirectional Transformations:International Summer School, Oxford, UK, July 25-29, 2016, Tutorial Lectures. International Summer School on Bidirectional Transformations, 2016, 25-29 Jul 2016 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , GBR , pp. 151-187.
Abstract
Bidirectional transformations, like software, need to be carefully engineered in order to provide guarantees about their correctness, completeness, acceptability and usability. This paper summarises a collection of lectures pertaining to engineering bidirectional transformations using Model-Driven Engineering techniques and technologies. It focuses on stages of a typical engineering lifecycle, starting with requirements and progressing to implementation and verification. It summarises Model-Driven Engineering approaches to capturing requirements, architectures and designs for bidirectional transformations, and suggests an approach for verification as well. It concludes by describing some challenges for future research into engineering bidirectional transformations.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 24 Apr 2018 12:00 |
Last Modified: | 17 Oct 2024 09:01 |
Published Version: | https://doi.org/10.1007/978-3-319-79108-1_5 |
Status: | Published online |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-319-79108-1_5 |
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Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:129991 |