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Titlebook: Computer Safety, Reliability, and Security; 40th International C Ibrahim Habli,Mark Sujan,Friedemann Bitsch Conference proceedings 2021 Spr

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樓主: Halloween
41#
發(fā)表于 2025-3-28 16:01:55 | 只看該作者
42#
發(fā)表于 2025-3-28 21:07:53 | 只看該作者
43#
發(fā)表于 2025-3-29 00:18:32 | 只看該作者
The Beecham Manual for Family Practicetion is then presented for the safety engineer. We demonstrate this SAHARA methodology using machine learning-based fault injection on a safety-critical use case of an adaptive cruise control system, to show that our approach can discover, visualise, and classify hazardous situations in a (semi-)automated manner in around twenty minutes.
44#
發(fā)表于 2025-3-29 05:44:15 | 只看該作者
45#
發(fā)表于 2025-3-29 07:42:30 | 只看該作者
46#
發(fā)表于 2025-3-29 13:04:34 | 只看該作者
The Beecham Manual for Family Practicehine learning for a comparatively simple function. This allowed the authors to develop a convincing assurance case, whilst identifying pragmatic considerations in the application of machine learning for safety-relevant functions.
47#
發(fā)表于 2025-3-29 15:58:26 | 只看該作者
The Beecham Manual for Family Practicele based on a real-world use-case. The proposed metrics, if they provide no advantage to guided test generation techniques over random ones, helped us trim the generated configuration landscape to identify safety gaps.
48#
發(fā)表于 2025-3-29 20:25:20 | 只看該作者
Towards Certified Analysis of Software Product Line Safety Casesroofs..We apply this infrastructure to formalize and lift a Change Impact Assessment (CIA) algorithm. We present a formal definition of the lifted algorithm, outline its correctness proof (with the full machine-checked proof available online), and discuss its implementation within a model management framework.
49#
發(fā)表于 2025-3-30 01:47:09 | 只看該作者
50#
發(fā)表于 2025-3-30 04:29:59 | 只看該作者
SASSI: Safety Analysis Using Simulation-Based Situation Coverage for Cobot Systemsle based on a real-world use-case. The proposed metrics, if they provide no advantage to guided test generation techniques over random ones, helped us trim the generated configuration landscape to identify safety gaps.
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