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Computation Platform for Automatic Analysis of Embedded Software Systems Using Model Based Approach

  • A. Dubey
  • X. Wu
  • H. Su
  • T. J. Koo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3707)

Abstract

In this paper, we describe a computation platform called ReachLab, which enables automatic analysis of embedded software systems that interact with continuous environment. Algorithms are used to specify how the state space of the system model should be explored in order to perform analysis. In ReachLab, both system models and analysis algorithm models are specified in the same framework using Hybrid System Analysis and Design Language (HADL), which is a meta-model based language. The platform allows the models of algorithms to be constructed hierarchically and promotes their reuse in constructing more complex algorithms. Moreover, the platform is designed in such a way that the concerns of design and implementation of analysis algorithms are separated. On one hand, the models of analysis algorithms are abstract and therefore the design of algorithms can be made independent of implementation details. On the other hand, translators are provided to automatically generate implementations from the models for computing analysis results based on computation kernels. Multiple computation kernels, which are based on specific computation tools such as d/dt and the Level Set toolbox, are supported and can be chosen to enable hybrid state space exploration. An example is provided to illustrate the design and implementation process in ReachLab.

Keywords

Directed Acyclic Graph Object Constraint Language Computation Kernel Abstract Syntax Discrete Mode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Henzinger, T.: The theory of hybrid automata. In: Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science, pp. 278–292 (1996)Google Scholar
  2. 2.
    Alur, R., Dill, D.L.: A theory of timed automata. Theoretical Computer Science 126, 183–235 (1994)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Henzinger, T.A., Majumdar, R.: A classification of symbolic transition systems. In: Proceedings of the 17th International Conference on Theoretical Aspects of Computer Science, pp. 13–34 (2000)Google Scholar
  4. 4.
    Mitchell, I., Templeton, J.A.: A toolbox of Hamilton-Jacobi solvers for analysis of nondeterministic continuous and hybrid systems. In: Morari, M., Thiele, L. (eds.) HSCC 2005. LNCS, vol. 3414, pp. 480–494. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Asarin, E., Dang, T., Maler, O.: The d/dt tool for verification of hybrid systems. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, pp. 365–370. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Karsai, G., Agrawal, A., Ledeczi, A.: A metamodel-driven MDA process and its tools. In: Workshop in Software Model Engineering (2003)Google Scholar
  7. 7.
    Karsai, G., Sztipanovits, J., Ledeczi, A., Bapty, T.: Model-integrated development of embedded software. Proceedings of the IEEE, 145–164 (2003)Google Scholar
  8. 8.
    Pinto, A., Sangiovanni-Vincentelli, A.L., Carloni, L.P., Passerone, R.: Interchange formats for hybrid systems: Review and proposal. In: Hespanha, J.P., Tiwari, A. (eds.) HSCC 2006. LNCS, vol. 3927, pp. 526–541. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Ledeczi, A., Maroti, M., Bakay, A., et al.: Generic modeling environment. In: International Workshop on Intelligent Signal Processing (2001)Google Scholar
  10. 10.
    Sztipanovits, J., Karsai, G., Biegl, C., Bapty, T., Ledeczi, A., Malloy, D.: Multigraph: an architecture for model-integrated computing. In: Proceedings of the 1st International Conference on Engineering of Complex Computer Systems, pp. 361–368 (1995)Google Scholar
  11. 11.
    Sztipanovits, J., Karsai, G., Franke, H.: Model-integrated program synthesis environment. In: Proceedings of the IEEE Symposium and Workshop on Engineering of Computer Based Systems, pp. 348–355 (1996)Google Scholar
  12. 12.
    Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn. The MIT Press, Cambridge (2001)zbMATHGoogle Scholar
  13. 13.
    Lygeros, J.: Lecture Notes on Hybrid Systems, Cambridge (2003)Google Scholar
  14. 14.
    Osher, S., Fedkiw, R.: Level Set Methods and Dynamic Implicit Surfaces. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  15. 15.
    Rantzer, A., Johansson, M.: Piecewise linear quadratic optimal control. IEEE Transactions on Automatic Control, 629–637 (2000)Google Scholar
  16. 16.
    Clark, T., Evans, A., Kent, S., Sammut, P.: The mmf approach to engineering object-oriented design languages. In: Workshop on Language Descriptions, Tools and Applications, LDTA, Genova, Italy (2001), Available via http://www.puml.org
  17. 17.
    Chen, K., Sztipanovits, J., Neema, S.: Toward a semantic anchoring infrastructure for domain-specific modeling languages. In: Fifth International Conference on Embedded Software (EMSOFT05), Jersey City, New Jersey (September 2005) (Accepted for publication)Google Scholar
  18. 18.
    Conrad, R.S., et al.: Object Constraint Language Specification ver 1.1 (September 1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • A. Dubey
    • 1
  • X. Wu
    • 1
  • H. Su
    • 1
  • T. J. Koo
    • 1
  1. 1.Embedded Computing Systems Laboratory, Institute for Software Integrated Systems, Department of Electrical Engineering and Computer ScienceVanderbilt UniversityNashville

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