TY - GEN
T1 - Verification model translation method toward behavior model for CAST
AU - Ando, Takahiro
AU - Wang, Bo
AU - Hisazumi, Kenji
AU - Kong, Weiqiang
AU - Fukuda, Akira
AU - Michiura, Yasutaka
AU - Sakemi, Keita
AU - Matsumoto, Michihiro
N1 - Funding Information:
In future work, we plan to apply our method to various examples and refine our translation rules based on feedback attained while doing so. Moreover, we plan to develop a translation method that translates state machine diagrams into parallel verification models rather than simple sequential models. Further, we plan to develop an automatic translation system that can translate the target objects into different types of models to meet different needs. ACKNOWLEDGMENT This work is partially supported by JSPS KAKENHI Grant Number JP15H05708.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/5
Y1 - 2018/12/5
N2 - In this study, we think the feature of exhaustively verifying the process model of model checking is effective for Causal Analysis based on Systems-Theoretic Accident Model and Process (CAST), and discuss the introduction of the model checking technology in CAST. In particular, we propose a verification model translation method for behavior models which are created in the CAST process. Because the interaction between multiple components is important in CAST, our translation method translates plural related SysML state machine diagrams describing the components behavior to one verification model. The verification model is described in Promela language for SPIN model checker. In order to suppress the cost of the model checking, our translation method has the feature that the verification model to be generated is simple. Furthermore, it has the feature that the correspondence between the related behavior models and the verification model is understandable, and the efficiency of the confirmation of verification result can be improved. In addition, since it has the feature that the communication situation between each state machine is easy to check, it is expected to be utilized for CAST. In this paper, we describe the rules to translate the related SysML state machine diagrams to a simple verification model in Promela.
AB - In this study, we think the feature of exhaustively verifying the process model of model checking is effective for Causal Analysis based on Systems-Theoretic Accident Model and Process (CAST), and discuss the introduction of the model checking technology in CAST. In particular, we propose a verification model translation method for behavior models which are created in the CAST process. Because the interaction between multiple components is important in CAST, our translation method translates plural related SysML state machine diagrams describing the components behavior to one verification model. The verification model is described in Promela language for SPIN model checker. In order to suppress the cost of the model checking, our translation method has the feature that the verification model to be generated is simple. Furthermore, it has the feature that the correspondence between the related behavior models and the verification model is understandable, and the efficiency of the confirmation of verification result can be improved. In addition, since it has the feature that the communication situation between each state machine is easy to check, it is expected to be utilized for CAST. In this paper, we describe the rules to translate the related SysML state machine diagrams to a simple verification model in Promela.
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U2 - 10.1109/DSA.2018.00032
DO - 10.1109/DSA.2018.00032
M3 - Conference contribution
AN - SCOPUS:85060696930
T3 - Proceedings - 2018 5th International Conference on Dependable Systems and Their Applications, DSA 2018
SP - 142
EP - 147
BT - Proceedings - 2018 5th International Conference on Dependable Systems and Their Applications, DSA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Dependable Systems and Their Applications, DSA 2018
Y2 - 22 September 2018 through 23 September 2018
ER -