Kaiserslautern - Fachbereich Informatik
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Most of the evolution in ambient assisted living is due to embedded
systems that dynamically adapt themself to react to environmental
changes or component/subsystem failures to maintain a certain level of
safety. Following this evolution fault tree analysis techniques have been
extended with concept for dynamic adaptation but resulting techniques
such as dynamic fault trees or state event fault trees analysis are not
widely used as expected.
In this report we describe a controlled experiment to analyze these two
techniques with regard to their applicability and efficiency in modeling
dynamic behavior of ambient assisted living systems.
Results of the experiment show that Dynamic Fault Trees are easier and more effective
to use, although they produce better results (models) with State Events Fault Trees.
Most innovation in the automotive industry is driven by embedded systems. They make usage of dynamic adaption to environmental changes or component/subsystem failures for remaining safe. Following this evolution, fault tree analysis techniques have been extended with concept for dynamic adaptation but resulting techniques like state event fault tree analysis, are not widely used in practice.
In this report we present the results of a controlled experiment that analyze these two techniques (State Events Fault Trees and Faul trees combined with markov chains) with regard to their applicability and efficiency in modeling dynamic behavior of dynamic embedded systems.
The experiment was conducted with students of the TU Kaiserslautern to modeli different safety aspects of an ambient assisted living system.
The main results of the experiment show that SEFTs where more easy and effective to use.