Risk management for high tech systems
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Abstract
How do we ensure that self-driving cars, nuclear power plants and Internet-of-things devices are safe and reliable? That is the topic of risk management. Fault tree analysis is a very popular technique here, deployed by many institutions like NASA, ESA, Honeywell, Ford, Airbus, the FDA, Toyota, Shell etc.
In this presentation, I will elaborate how the deployment of stochastic model checking can improve the capabilities of fault tree analysis, making them more powerful, flexible and efficient, allowing one to analyze a richer variety of questions faster, and thereby increasing their practical relevance and deployment in practical risk assessments.
I will report on our experience with the application and validation of these techniques in industrial practice. In particular, I will show how compositionally, model-driven engineering, graph rewriting all helped to crunch industrial cases. Finally, I will present some new directions on the deployment of big data analytics within fault tree analysis.
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Information & Contributors
Information
Published In
June 2018
101 pages
ISBN:9781450357180
DOI:10.1145/3193992
- General Chairs:
- Stefania Gnesi,
- Nico Plat,
- Program Chairs:
- Paola Spoletini,
- Patrizio Pelliccione
Copyright © 2018 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
- SIGSOFT: ACM Special Interest Group on Software Engineering
- IEEE-CS: Computer Society
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 02 June 2018
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Conference
ICSE '18
Sponsor:
- SIGSOFT
- IEEE-CS
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