Chang, Wanli orcid.org/0000-0002-4053-8898, Zhao, Shuai, Wei, Ran et al. (2 more authors) (2019) From Java to real-time Java:A model-driven methodology with automated toolchain. In: LCTES 2019::Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems. 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems, 22 Jun 2019 ACM , USA , pp. 123-134.
Abstract
Real-time systems are receiving increasing attention with the emerging application scenarios that are safety-critical, complex in functionality, high on timing-related performance requirements, and cost-sensitive, such as autonomous vehicles. Development of real-time systems is error-prone and highly dependent on the sophisticated domain expertise, making it a costly process. There is a trend of the existing software without the real-time notion being re-developed to realise real-time features, e.g., in the big data technology. This paper utilises the principles of model-driven engineering (MDE) and proposes the first methodology that automatically converts standard time-sharing Java applications to real-time Java applications. It opens up a new research direction on development automation of real-time programming languages and inspires many research questions that can be jointly investigated by the embedded systems, programming languages as well as MDE communities.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Copyright held by the owner/author(s). 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 > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 13 Feb 2020 13:00 |
Last Modified: | 21 Nov 2024 00:20 |
Published Version: | https://doi.org/10.1145/3316482.3326360 |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/3316482.3326360 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157050 |