A workflow for automatically generating application-level safety mechanisms from UML stereotype model representations
Autor(en): | Huning, L. Iyenghar, P. Pulvermueller, E. |
Herausgeber: | Ali, R. Kaindl, H. Maciaszek, L. |
Stichwörter: | Automatic Generation; Automatically generated; Code Generation; Embedded Software Engineering; Embedded Systems; Fault detection; Functional Safety; Model driven development; Model representation; Model-Driven Development; Quantitative experiments; Safety critical systems; Safety mechanisms, Safety engineering; Security systems; Software engineering; Unified Modeling Language, Application level; Voting | Erscheinungsdatum: | 2020 | Herausgeber: | SciTePress | Journal: | ENASE 2020 - Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering | Startseite: | 216 | Seitenende: | 228 | Zusammenfassung: | Safety-critical systems operate in contexts where failure may lead to serious harm for humans or the environment. Safety standards, e.g., IEC 61508 or ISO 26262, provide development guidelines to improve the safety of such systems. For this, they recommend a variety of safety mechanisms to mitigate possible safety hazards. While these standards recommend certain safety mechanisms, they do not provide any concrete development or implementation assistance for any of these techniques. This paper presents a detailed workflow, how such safety mechanisms may be automatically generated from UML model representations in a model-driven development process. We illustrate this approach by applying it to the modeling and automatic generation of voting mechanisms, which are a wide-spread safety mechanism in safety-critical systems that employ some form of redundancy for fault detection or fault masking. Finally, we study the scalability of the proposed code generation via quantitative experiments. © Copyright 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. |
Beschreibung: | Conference of 15th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2020 ; Conference Date: 5 May 2020 Through 6 May 2020; Conference Code:160383 |
ISBN: | 9789897584213 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088393319&partnerID=40&md5=da377d2e2047f31f8b998aa41a482717 |
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geprüft am 30.04.2024