Computation Platform for Automatic Analysis of Embedded Software Systems Using Model Based Approach
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.
KeywordsDirected Acyclic Graph Object Constraint Language Computation Kernel Abstract Syntax Discrete Mode
Unable to display preview. Download preview PDF.
- 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
- 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
- 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.Karsai, G., Sztipanovits, J., Ledeczi, A., Bapty, T.: Model-integrated development of embedded software. Proceedings of the IEEE, 145–164 (2003)Google Scholar
- 9.Ledeczi, A., Maroti, M., Bakay, A., et al.: Generic modeling environment. In: International Workshop on Intelligent Signal Processing (2001)Google Scholar
- 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.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
- 13.Lygeros, J.: Lecture Notes on Hybrid Systems, Cambridge (2003)Google Scholar
- 15.Rantzer, A., Johansson, M.: Piecewise linear quadratic optimal control. IEEE Transactions on Automatic Control, 629–637 (2000)Google Scholar
- 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.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.Conrad, R.S., et al.: Object Constraint Language Specification ver 1.1 (September 1997)Google Scholar