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Analysis of Utilization Methods of the Statistical Model Checking Results for Localizing Faults on System of Systems
Sangwon Hyun, Yong-jun Shin, Doo-Hwan Bae
http://doi.org/10.5626/JOK.2020.47.4.380
System of Systems (SoS) is a large and complex system comprising independent constituent systems. Statistical Model Checking (SMC) techniques can be used to verify if the SoS achieves its goals or not. However, even if the SoS goal failure is detected using the SMC, finding a root cause of the SoS failure requires more cost than that of a system. One of the candidate solutions for reducing the debugging cost is to apply fault localization techniques on the SoS. However, existing fault localization techniques are designed to utilize testing results of a system. Thus, a method to utilize SMC results is needed to apply existing fault localization techniques to the SoS. In this study, we suggest six utilization methods of SMC results for SoS fault localization, and compare the performance of them on the emergency-response SoS. We found that the method based on the expectation value showed the best performance in the experiment.
Analysis of Case Scenario to Develop a System of Systems Meta-model for Ontology Representation
Young-Min Baek, Sumin Park, Yong-Jun Shin, Doo-Hwan Bae
http://doi.org/10.5626/JOK.2018.45.10.1056
Ontology is a formal and explicit specification technique that defines concepts and relationships of a system. It is utilized to establish a common knowledge base and to reduce mismatches or inconsistencies during communication. Since a System-of-Systems (SoS) is a large-scale complex system that achieves higher-level common goals by the collaboration of constituent systems, ontologies need to be established for overall SoS development and operations. In other words, refined development and communications among various stakeholders of an SoS can be achieved based on the conceptualization power of an ontology. However, in order to build an ontology effectively, SoS engineers require a systematic means to provide a guideline for domain analysis and ontology establishment. To fulfill these requirements, this study proposes a meta-model, called the Meta-model for System-of- Systems (M2SoS), which enables systematic specifications of ontologies for SoS development. M2SoS is developed based on existing studies on meta-modeling approaches in the multi-agent system domain, but M2SoS is improved to meet SoS-specific requirements by SoS case analysis.
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