Mining of Extended Signal Temporal Logic Specifications with ParetoLib 2.0

Abstract

This paper presents ParetoLib 2.0, a Python tool for offline monitoring and specification mining of cyber-physical systems. ParetoLib 2.0 uses Signal Temporal Logic (STL) as the formalism for specifying properties on time series. ParetoLib 2.0 builds upon other tools for evaluating and mining STL expressions, and extends them with new functionalities. In particular, ParetoLib 2.0 implements a novel mining algorithm that relies on a set of new quantitative operators for trace analysis in STL as well as an original graphical user interface. Finally, the performance is optimized with respect to previous releases of the tool.