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