Paige, Richard F. orcid.org/0000-0002-1978-9852, Zolotas, Athanasios, Kolovos, Dimitrios S. orcid.org/0000-0002-1724-6563 et al. (4 more authors) (2018) SECT-AIR:Software Engineering Costs and Timescales – Aerospace Initiative for Reduction. In: Software Technologies: Applications and Foundations - STAF 2017 Collocated Workshops, Revised Selected Papers. International conference on Software Technologies: Applications and Foundations, STAF 2017, 17-21 Jul 2017 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , DEU , pp. 403-408.
Abstract
Software is critical to the majority of functionality in avionics and aerospace systems. The amount of safety-related software in avionics is growing rapidly (doubling in size around every four years), and the costs of software programmes in industry are increasingly unaffordable – safety-related code can cost upwards of USD 150 per line. At the same time, demands from avionics customers for increased scope and new functionality is increasing, and quality is non-negotiable: it is fixed by standards and safety requirements. The SECT-AIR project is addressing these cost and demand issues by focusing on automation in software engineering, with particular emphasis on model-based development. In this paper we provide an overview of the motivation behind the project, which started in 2016, and some of the key tasks it will carry out to help improve productivity, increase customer scope and maintain quality.
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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. |
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: | 25 Apr 2024 09:00 |
Last Modified: | 13 Nov 2024 09:23 |
Published Version: | https://doi.org/10.1007/978-3-319-74730-9_36 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-319-74730-9_36 |
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Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:211855 |
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