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Runtime safety analysis for safe reconfiguration

Authors: Claudia Priesterjahn; Christian Heinzemann; Wilhelm Schäfer; Matthias Tichy;

Runtime safety analysis for safe reconfiguration

Abstract

Modern technical systems are increasingly built to exhibit self-x properties as, e.g., self-healing or self-optimization. For this, they require adaptation at runtime. This is even true for embedded or mechatronic systems which often operate in safety-critical environments. There, the effects of the adaptation with respect to safety must be analyzed carefully. However, not all parameters needed for safety analyses, e.g., the concrete system architecture, are known at design time. Consequently, safety analyses need to be executed during runtime. Current approaches of runtime safety analysis typically react to anomalies that already occurred in the system. Thus, unsafe system states cannot be excluded completely. We present a runtime safety analysis that prevents system states with an unacceptable risk that have not yet occurred. For this, we generate the reachable component structures at runtime and analyze them with respect to risk. The system is modified such that component structures with an unacceptable risk are not reachable any more and are thus prevented.

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    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Top 10%
Top 10%
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