Analytical toolset for model-based stochastic error propagation analysis: extension and optimization towards industrial requirements

T. I. Fabarisov, N. I. Yusupova, K. Ding, A. Morozov, K. Janschek

Аннотация


Model-Based System Engineering (MBSE) is a popular mathematical and visual approach to the design of complex control, signal processing, and communication systems. It is used in safety critical industrial domains including aerospace, automotive, transportation, medical and robotics applications. Our group develops methods and tools for model-based system reliability and safety analysis with the main focuses on stochastic modelling of error propagation processes. This article is devoted to the optimisation and extensions to our analytical toolset. We have investigated the key modeling paradigms, requirements and industrial needs and have formulated the list of particular extensions.


Ключевые слова


Error propagation model; reliability; safety; dependability; model-based systems; model-based analysis; control flow; data flow; optimization

Полный текст:

PDF (English)

Литература


Gianni, Daniele; D'Ambrogio, Andrea; Tolk, Andreas, eds. Modeling and Simulation-Based Systems Engineering Handbook (1 ed.). USA: CRC Press, 2014.

A. Morozov and K. Janschek. Dual graph error propagation model for mechatronic system analysis. In 18th IFAC World Congress, Milano, Italy, pp. 9893-9898, 2011.

A. Morozov, R. Tuk, and K. Janschek. ErrorPro: Software Tool for Stochastic Error Propagation Analysis. In 1st International Workshop on Resiliency in Embedded Electronic Systems, Amsterdam, The Netherlands, pp. 59-60, 2015.

Marta Kwiatkowska, Gethin Norman and David Parker. PRISM 4.0: Verification of Probabilistic Real-time Systems. In Proc. 23rd International Conference on Computer Aided Verification (CAV’11), volume 6806 of LNCS, pp. 585-591, Springer, 2011.

Katoen J P, Zapreev I S, Hahn E M, et al. The ins and outs of the probabilistic model checker MRMC[J]. Performance evaluation, 2011, 68(2): 90-104.

Bozzano M, Cimatti A, Katoen J P, et al. The COMPASS Approach: Correctness, Modelling and Performability of Aerospace Systems[C]//SAFECOMP. 2009, 5775: 173-186.

Arnold A, Point G, Griffault A, et al. The AltaRica formalism for describing concurrent systems[J]. Fundamenta Informaticae, 1999, 40(2, 3): 109-124.

OMG. OMG Unified Modeling Language (OMG UML), 2015.

A. Morozov and K. Janschek. Case study results for probabilistic error propagation analysis of a mechatronic system, In: Tagungsband VDI Fachtagung Mechatronik 2013, Aachen, 06.03.-08.03.2013, pp. 229-234.

A. Morozov and K. Janschek. Probabilistic error propagation model for mechatronic systems. Mechatronics, 24(8):1189 – 1202, 2014.

A. Morozov, K. Janschek, T. Krüger, A. Schiele. Stochastic Error Propagation Analysis of Model-driven Space Robotic Software Implemented in Simulink. In Proceedings of the Third Workshop on Model-driven Robot Software Engineering, Leipzig, Germany, 2016.

Morozov, A., Ding, K., Chen T. and Janschek, K. Test Suite Prioritization for Efficient Regression Testing of Model-based Automotive Software. Accepted paper. Proceedings of the annual conference on Software Analysis, Testing and Evolution (SATE), Harbin, China, 2017.

K. Ding, T. Mutzke, A. Morozov, and K. Janschek. Automatic Transformation of UML System Models for Model-based Error Propagation Analysis of Mechatronic Systems. In Proceedings of 7th IFAC Symposium on Mechatronic Systems, Loughborough University, UK, 2016.

T. Mutzke, K. Ding, A. Morozov, K. Janschek, J. Braun. Model-based Analysis of Timing Errors for Reliable Design of Mechatronic Medical Devices, In Proceedings of 3rd International Conference on Control and Fault-Tolerant Systems, Barcelona, Catalonia, 2016.

A. Morozov, K. Janschek. Flight Control Software Failure Mitigation: Design Optimization for Software-implemented Fault Detectors. In Proceedings of 20th IFAC Symposium on Automatic Control in AerospaceACA 2016 — Sherbrooke, Quebec, Canada, 21-25 August 2016.

Zhao F, Morozov A, Yusupova N I, et al. Nesting algorithm for dual-graph error propagation models[C]//CSIT'2016. 2016:р.р.106-110.

B. Lewis, P. Feller. Impact of Architectural Model-Based Engineering with AADL, Carnegie Mellon University, 2007.

Zou L., Zhan N., Wang S., Fränzle M. Formal Verification of Simulink/Stateflow Diagrams. In: Finkbeiner B., Pu G., Zhang L. (eds) Automated Technology for Verification and Analysis. Lecture Notes in Computer Science, vol 9364. Springer, Cham, 2015.

Chris Lattner Vikram Adve. LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation. University of Illinois at Urbana-Champaign.

Delligatti, Lenny. SysML Distilled. A Brief Guide to the Systems Modeling Language. — Addison-Wesley Professional, 2013.

Morozov, Andrey & Janschek, Klaus & Krüger, Thomas & Schiele, André. (2016). Stochastic Error Propagation Analysis of Model-driven Space Robotic Software Implemented in Simulink. MORSE '16. Proceedings of the 3rd Workshop on Model-Driven Robot Software Engineering: 24-31.


Ссылки



(c) 2019 T. I. Fabarisov, N. I. Yusupova, K. Ding, A. Morozov, K. Janschek