Abstract
This paper introduces a new lightweight tool for simulative error propagation analysis of Simulink models. The tool allows a user to inject different types of faults that are common for embedded control systems and analyze error propagation to critical system parts and outputs. The intended workflow comprises the following three steps: (i) setup faulty and critical blocks of a Simulink model, (ii) setup and run simulations, and (iii) observe and examine the obtained results. The tool is implemented in MATLAB using the callback block functions from the Simulink API. The graphical user interface allows the injection of several types of faults including computing hardware faults such as single and multiple bit-flips, sensor faults such as offsets, stuck-at faults, and a noise, and network faults such as time delays and packet drops. The fault occurrence and duration can be specified either with the classical reliability metrics like mean time to failure and mean time to repair, or failure rates with classical (normal, exponential, Poisson, Weibull etc.) or custom user-defined probability distributions. The error propagation to the selected critical blocks is reported with several statistical metrics including the mean number of errors, failure rate, and mean error value, as well as performance indexes such as integral squared error, integral absolute error, and integral time-weighted absolute error. The reported numerical results support standard reliability and safety assessment methods such as fault tree analysis and failure mode and effects analysis. The paper demonstrates the tool with a case study Simulink model of fault-tolerant control for a passenger jet.
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References
Avizienis, A., Laprie, J.C., Randell, B., Landwehr, C.: Basic concepts and taxonomy of dependable and secure computing. IEEE Trans. Dependable Secure Comput. 1(1), 11–33 (2004)
Fey, I., Müller, J.: Model-based design for safety-related applications (2008)
Hsueh, M.C., Tsai, T.K., Iyer, R.K.: Fault injection techniques and tools. Computer 30(4), 75–82 (1997)
Joshi, A., Heimdahl, M.P.E.: Model-based safety analysis of simulink models using SCADE design verifier. In: Winther, R., Gran, B.A., Dahll, G. (eds.) SAFECOMP 2005. LNCS, vol. 3688, pp. 122–135. Springer, Heidelberg (2005). doi:10.1007/11563228_10
Kooli, M., Di Natale, G.: A survey on simulation-based fault injection tools for complex systems. In: 2014 9th IEEE International Conference on Design & Technology of Integrated Systems In: Nanoscale Era (DTIS), pp. 1–6. IEEE (2014)
MathWorks: IEC Certification Kit. http://www.mathworks.de/products/iec-61508/
MathWorks: Matlab & simulink: Simulink users guide r2016a (2016)
Mathworks: Develop, manage, and execute simulation-based tests (2017). https://www.mathworks.com/products/simulink-test.html
Mathworks: Fault-tolerant control of a passenger jet - matlab simulink example (2017). https://de.mathworks.com/help/control/examples/fault-tolerant-control-of-a-passenger-jet.html
Misra, A.: Sl sf modeling design and style guidelines for the application of simulink and stateflow. V1. 0, MIRA (2009)
Natella, R., Cotroneo, D., Madeira, H.S.: Assessing dependability with software fault injection: a survey. ACM Comput. Surv. (CSUR) 48(3), 44 (2016)
Skarin, D., Vinter, J., Svenningsson, R.: Visualization of model-implemented fault injection experiments. In: Bondavalli, A., Ceccarelli, A., Ortmeier, F. (eds.) SAFECOMP 2014. LNCS, vol. 8696, pp. 219–230. Springer, Cham (2014). doi:10.1007/978-3-319-10557-4_25
Svenningsson, R., Vinter, J., Eriksson, H., Törngren, M.: MODIFI: a model-implemented fault injection tool. In: Schoitsch, E. (ed.) SAFECOMP 2010. LNCS, vol. 6351, pp. 210–222. Springer, Heidelberg (2010). doi:10.1007/978-3-642-15651-9_16
Vinter, J., Bromander, L., Raistrick, P., Edler, H.: Fiscade-a fault injection tool for scade models. In: 2007 3rd Institution of Engineering and Technology Conference on Automotive Electronics, pp. 1–9. IET (2007)
Vulinovic, S., Schlingloff, B.H.: Model based dependability evaluation for automotive control functions. In: Invited Session: Model-Based Design and Test, 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Florida (2005)
Ziade, H., Ayoubi, R.A., Velazco, R., et al.: A survey on fault injection techniques. Int. Arab J. Inf. Technol. 1(2), 171–186 (2004)
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Saraoğlu, M., Morozov, A., Söylemez, M.T., Janschek, K. (2017). ErrorSim: A Tool for Error Propagation Analysis of Simulink Models. In: Tonetta, S., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2017. Lecture Notes in Computer Science(), vol 10488. Springer, Cham. https://doi.org/10.1007/978-3-319-66266-4_16
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DOI: https://doi.org/10.1007/978-3-319-66266-4_16
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