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Increasing Dependability by Means of Model-Based Acceptance Test inside RTOS

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Parallel Processing and Applied Mathematics (PPAM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3911))

Abstract

Component-based self-optimizing systems can adjust themselves over time to dynamic environments by means of exchanging components. In case that such systems are safety-critical, the dependability issue becomes paramountly significant. This paper presents a novel model-based runtime verification to increase dependability for the self-optimizing systems of this kind. The proposed verification approach plays a role of an alternative acceptance test transparently integrated in RTOS, named model-based acceptance test. The verification is performed at the level of (RT-UML) models representing the systems under consideration. The properties to be checked are expressed by RT-OCL where the underlying temporal logic is restricted to either time-annotated ACTL or LTL formulae. The applied technique is based on the on-the-fly model checking, which runs interleaved with the execution of the checked system in a pipelined manner. More specifically, for ACTL formulae this means an on-the-fly solution to the NHORNSAT problem, while in the case of LTL formulae, the emptiness checking method is applied.

This work is developed in the course of the Collaborative Research Center 614 – Self-Optimizing Concepts and Structures in Mechanical Engineering – Paderborn University, and is published on its behalf and funded by the Deutsche Forschungsgemeinschaft.

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Zhao, Y., Oberthür, S., Montealegre, N., Rammig, F.J., Kardos, M. (2006). Increasing Dependability by Means of Model-Based Acceptance Test inside RTOS. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2005. Lecture Notes in Computer Science, vol 3911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752578_125

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  • DOI: https://doi.org/10.1007/11752578_125

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34141-3

  • Online ISBN: 978-3-540-34142-0

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