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Abstract

Model checking can be applied to finite state systems in order to find counterexamples showing that they do not satisfy their specification. This was generalized to handle parametric systems under some given constraints, usually using some inductive argument. However, even in the restricted cases where these parametric methods apply, the assumption is usually of a simple fixed architecture, e.g., a ring. We consider the case of nontrivial architectures for communication protocols, for example, achieving a multiparty interaction between arbitrary subsets of processes. In this case, an error may manifest itself only under some particular architectures and interactions, and under some specific values of parameters. We apply here our model checking based genetic programming approach for achieving a dual task: finding an instance of a protocol which is suspicious of being bogus, and automatically correcting the error. The synthesis tool we constructed is capable of generating various mutations of the code. Moving between them is guided by model checking analysis. In the case of searching for errors, we mutate only the architecture and related parameters, and in the case of fixing the error, we mutate the code further in order to search for a corrected version. As a running example, we use a realistic nontrivial protocol for multiparty interaction. This protocol, published in a conference and a journal, is used as a building block for various systems. Our analysis shows this protocol to be, as we suspected, erroneous; specifically, the protocol can reach a livelock situation, where some processes do not progress towards achieving their interactions. As a side effect of our experiment, we provide a correction for this important protocol obtained through our genetic process.

Keywords

Model Check Genetic Programming Mutual Exclusion Partial Order Reduction Message Sequence Chart 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gal Katz
    • 1
  • Doron Peled
    • 1
  1. 1.Department of Computer ScienceBar Ilan UniversityRamat GanIsrael

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