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Efficient Guiding Strategies for Testing of Temporal Properties of Hybrid Systems

  • Tommaso Dreossi
  • Thao Dang
  • Alexandre Donzé
  • James Kapinski
  • Xiaoqing Jin
  • Jyotirmoy V. Deshmukh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9058)

Abstract

Techniques for testing cyberphysical systems (CPS) currently use a combination of automatic directed test generation and random testing to find undesirable behaviors. Existing techniques can fail to efficiently identify bugs because they do not adequately explore the space of system behaviors. In this paper, we present an approach that uses the rapidly exploring random trees (RRT) technique to explore the state-space of a CPS. Given a Signal Temporal Logic (STL) requirement, the RRT algorithm uses two quantities to guide the search: The first is a robustness metric that quantifies the degree of satisfaction of the STL requirement by simulation traces. The second is a metric for measuring coverage for a dense state-space, known as the star discrepancy measure. We show that our approach scales to industrial-scale CPSs by demonstrating its efficacy on an automotive powertrain control system.

Keywords

Temporal Logic Star Discrepancy Guide Strategy Simulation Trace Goal Cell 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Tommaso Dreossi
    • 1
  • Thao Dang
    • 1
  • Alexandre Donzé
    • 2
  • James Kapinski
    • 3
  • Xiaoqing Jin
    • 3
  • Jyotirmoy V. Deshmukh
    • 3
  1. 1.VerimagGièresFrance
  2. 2.University of CaliforniaBerkeleyUSA
  3. 3.Toyota Technical CenterAnn ArborUSA

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