Download PDFOpen PDF in browser

Automated analysis of Stateflow models

18 pagesPublished: May 4, 2017

Abstract

Stateflow is a widely used modeling framework for embedded and cyberphysical systems where control software interacts with physical processes. In this work, we present a framework and a fully automated safety verification technique for Stateflow models. Our approach is two-folded: (i) we faithfully compile Stateflow models into hierarchical state machines, and (ii) we use automated logic-based verification engine to decide the validity of safety properties. The starting point of our approach is a denotational semantics of Stateflow. We propose a compilation process using continuation-passing style (CPS) denotational semantics. Our compilation technique preserves the structural and modal behavior of the system. The overall approach is implemented as an open source toolbox that can be integrated into the existing Mathworks Simulink/Stateflow modeling framework. We present preliminary experimental evaluations that illustrate the effectiveness of our approach in code generation and safety verification of industrial scale Stateflow models.

Keyphrases: continuation passing style, model checking, stateflow

In: Thomas Eiter and David Sands (editors). LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 46, pages 144-161.

BibTeX entry
@inproceedings{LPAR-21:Automated_analysis_Stateflow_models,
  author    = {Hamza Bourbouh and Pierre-Loic Garoche and Christophe Garion and Arie Gurfinkel and Temesghen Kahsai and Xavier Thirioux},
  title     = {Automated analysis of Stateflow models},
  booktitle = {LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Thomas Eiter and David Sands},
  series    = {EPiC Series in Computing},
  volume    = {46},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/fPz},
  doi       = {10.29007/b8gq},
  pages     = {144-161},
  year      = {2017}}
Download PDFOpen PDF in browser