In this paper, we present a tool for monitoring the traces of cyber-physical systems (CPS) at runtime, with respect to Signal Temporal Logic (STL) specifications. Our tool is based on the recent advances of causation monitoring, which reports not only whether an executing trace violates the specification, but also how relevant the increment of the trace at each instant is to the specification violation. In this way, it can deliver more information about system evolution than classic online robust monitors. Moreover, by adapting two dynamic programming strategies, our implementation significantly improves the efficiency of causation monitoring, allowing its deployment in practice. The tool is implemented as a C++ executable and can be easily adapted to monitor CPS in different formalisms. We evaluate the efficiency of the proposed monitoring tool, and demonstrate its superiority over existing robust monitors in terms of the information it can deliver about system evolution.

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CauMon: An Informative Online Monitor for Signal Temporal Logic

  • Zhenya Zhang,
  • Jie An,
  • Paolo Arcaini,
  • Ichiro Hasuo

摘要

In this paper, we present a tool for monitoring the traces of cyber-physical systems (CPS) at runtime, with respect to Signal Temporal Logic (STL) specifications. Our tool is based on the recent advances of causation monitoring, which reports not only whether an executing trace violates the specification, but also how relevant the increment of the trace at each instant is to the specification violation. In this way, it can deliver more information about system evolution than classic online robust monitors. Moreover, by adapting two dynamic programming strategies, our implementation significantly improves the efficiency of causation monitoring, allowing its deployment in practice. The tool is implemented as a C++ executable and can be easily adapted to monitor CPS in different formalisms. We evaluate the efficiency of the proposed monitoring tool, and demonstrate its superiority over existing robust monitors in terms of the information it can deliver about system evolution.