TY - GEN
T1 - Identifying safety properties guaranteed in changed environment at runtime
AU - Aizawa, Kazuya
AU - Tei, Kenji
AU - Honiden, Shinichi
N1 - Funding Information:
VIII. ACKNOWLEDGMENT The research was partially supported by National Institute of Information and Communications Technology (NICT) and JSPS KAKENHI.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/10
Y1 - 2018/9/10
N2 - Safety properties for systems are guaranteed under assumptions to an environment. If the assumptions are broken at runtime, the safety properties are no longer guaranteed. The system should adapt to the changes in order to guarantee the safety properties or relaxed safety properties. Our purpose is establishing techniques to identify the maximum level of safety properties that can be guaranteed in a changed environment. The technique should be efficient so that it is applicable to runtime usage. In this paper, we propose an efficient algorithm that identifies the maximum level of safety properties. Our idea is analyzing availability of each safety property guarantee at a time and restricting analysis only in changed part of the previous result, instead of analysis from the scratch. We extend an existing analysis algorithm based on two-player game to realize the difference analysis. We evaluate our algorithm in terms of (1) level of safety properties and (2) computational time through two case studies.
AB - Safety properties for systems are guaranteed under assumptions to an environment. If the assumptions are broken at runtime, the safety properties are no longer guaranteed. The system should adapt to the changes in order to guarantee the safety properties or relaxed safety properties. Our purpose is establishing techniques to identify the maximum level of safety properties that can be guaranteed in a changed environment. The technique should be efficient so that it is applicable to runtime usage. In this paper, we propose an efficient algorithm that identifies the maximum level of safety properties. Our idea is analyzing availability of each safety property guarantee at a time and restricting analysis only in changed part of the previous result, instead of analysis from the scratch. We extend an existing analysis algorithm based on two-player game to realize the difference analysis. We evaluate our algorithm in terms of (1) level of safety properties and (2) computational time through two case studies.
KW - Discrete controller synthesis
KW - Safety property
KW - Self-Adaptive
UR - http://www.scopus.com/inward/record.url?scp=85054511621&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054511621&partnerID=8YFLogxK
U2 - 10.1109/AGENTS.2018.8460083
DO - 10.1109/AGENTS.2018.8460083
M3 - Conference contribution
AN - SCOPUS:85054511621
SN - 9781538681800
T3 - Proceedings - 2018 IEEE International Conference on Agents, ICA 2018
SP - 75
EP - 80
BT - Proceedings - 2018 IEEE International Conference on Agents, ICA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Agents, ICA 2018
Y2 - 28 July 2018 through 31 July 2018
ER -