DocumentCode :
3677721
Title :
Runtime Model-Based Safety Analysis of Self-Organizing Systems with S#
Author :
Axel Habermaier;Benedikt Eberhardinger;Hella Seebach;Johannes Leupolz;Wolfgang Reif
Author_Institution :
Inst. for Software &
fYear :
2015
Firstpage :
128
Lastpage :
133
Abstract :
Self-organizing systems present a challenge for model-based safety analysis techniques: At design time, the potential system configurations are unknown, making it necessary to postpone the safety analyses to runtime. At runtime, however, model checking based safety analysis techniques are often too time-consuming because of the large state spaces that have to be analyzed. Based on the S# framework´s support for runtime model adaptation, we modularize runtime safety analyses by splitting them into two parts, modeling and analyzing the self-organizing and non-self-organizing parts separately. With some additional heuristics, the resulting state space reduction facilitates the use of model checking based safety analysis techniques to analyze the safety of self-organizing systems. We outline this approach on a self-organizing production cell, assessing the self-organization´s impact on the overall safety of the system.
Keywords :
"Analytical models","Adaptation models","Runtime","Hazards","Robot kinematics"
Publisher :
ieee
Conference_Titel :
Self-Adaptive and Self-Organizing Systems Workshops (SASOW), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SASOW.2015.26
Filename :
7306569
Link To Document :
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