Prioritizing Scenarios based on STAMP/STPA Using Statistical Model Checking

Recently, a hazard analysis technique STAMP/STPA has been widely accepted since it is recognized as being suitable for software-intensive systems. Using STAMP/STPA, we can find hazardous scenarios of the target system that cannot be obtained by other traditional hazard analysis methods and those scenarios can be used for validation testing. However, generally the number of obtained scenarios can be huge and the validation testing involves a considerable cost. In this study, we propose a method to prioritize hazardous scenarios identified by STAMP/STPA with the help of a statistical model-checking technique. We give a procedure for systematically transforming the model defined by STAMP/STPA to a formal model for a statistical model-checking tool. We also show the usefulness of the proposed method using an example of train gate control system.

[1]  Ulrich Eberle,et al.  Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles , 2018 .

[2]  Sarah J. Dunnett,et al.  Event-tree analysis using binary decision diagrams , 2000, IEEE Trans. Reliab..

[3]  Stefan Wagner,et al.  A comprehensive safety engineering approach for software-intensive systems based on STPA , 2015, ArXiv.

[4]  Kim G. Larsen,et al.  Uppaal SMC tutorial , 2015, International Journal on Software Tools for Technology Transfer.

[5]  Thomas Hérault,et al.  Approximate Probabilistic Model Checking , 2004, VMCAI.

[6]  Cyrille Jégourel,et al.  Importance Splitting for Statistical Model Checking Rare Properties , 2013, CAV.

[7]  Marta Z. Kwiatkowska,et al.  PRISM: Probabilistic Symbolic Model Checker , 2002, Computer Performance Evaluation / TOOLS.

[8]  Mariëlle Stoelinga,et al.  Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools , 2014, Comput. Sci. Rev..

[9]  Brian Veitch,et al.  Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[10]  Axel Legay,et al.  Statistical Model Checking , 2019, Computing and Software Science.

[11]  Edmund M. Clarke,et al.  Model Checking , 1999, Handbook of Automated Reasoning.

[12]  Bohus Leitner,et al.  A General Model for Railway Systems Risk Assessment with the Use of Railway Accident Scenarios Analysis , 2017 .

[13]  Antonio Coronato,et al.  Towards a Probabilistic Model Checking-based approach for Medical Device Risk Assessment , 2015, 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings.

[14]  Emilia Villani,et al.  System safety assessment based on STPA and model checking , 2018, Safety Science.

[15]  Kyle Post,et al.  Integrating SOTIF and Agile Systems Engineering , 2019 .

[16]  Axel Legay,et al.  Statistical Model Checking: An Overview , 2010, RV.

[17]  Michael W. Whalen,et al.  Model-Based Safety Analysis , 2013 .

[18]  Fausto Giunchiglia,et al.  NUSMV: A New Symbolic Model Verifier , 1999, CAV.

[19]  Kirsten Winter,et al.  Probabilistic Model-Checking Support for FMEA , 2007 .