Ali, Qurat Ul Ain (Accepted: 2021) Heterogeneous Model Query Optimisation. In: MODELS 2021: Model-Driven Engineering Languages and Systems, proceedings:. MODELS, 10-15 Oct 2021 IEEE , JPN (In Press)
Abstract
With the growing size and complexity of software systems, the underlying models also grow in size proportionally. These large-scale models pose scalability issues for model-driven engineering technologies. These models can be persisted in various backend technologies (such as file systems, document and relational databases) and can be represented in different formats such as XMI and Flexmi. Several tailored high-level model management languages such as OCL and EOL enable developers to work on different backend technologies in a uniform way by shielding them from the complexities of different backends. On the contrary, performance with respect to execution time in tailored model management languages programs becomes one of the major scalability bottlenecks. In this work, we propose an architecture built on top of existing model query languages to facilitate query optimisation. The proposed approach will benefit from compile-time static analysis and automatic program rewrit- ing to optimise queries operating over heterogeneous backend technologies. Optimisation strategies and performance will vary depending on the type of queries and the backend modelling technology. We expect to significantly improve performance (decrease in one order of magnitude of execution time) for model management programs, particularly over large-scale models.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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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 |
Keywords: | model-driven engineering,static analysis,model querying |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 03 Nov 2021 10:50 |
Last Modified: | 07 Feb 2025 00:08 |
Status: | In Press |
Publisher: | IEEE |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179962 |
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