Automated Verification and Synthesis of Stochastic Hybrid Systems: A Survey

TL;DR

This survey reviews recent advances in automated verification and synthesis methods for stochastic hybrid systems, highlighting approaches, tools, challenges, and future research directions in this complex field.

Contribution

It provides a comprehensive overview of recent techniques, tools, and open problems in the analysis and synthesis of stochastic hybrid systems, guiding new researchers.

Findings

Overview of diverse verification and synthesis approaches

Discussion of software tools implementing these methods

Identification of open challenges and future directions

Abstract

Stochastic hybrid systems have received significant attentions as a relevant modelling framework describing many systems, from engineering to the life sciences: they enable the study of numerous applications, including transportation networks, biological systems and chemical reaction networks, smart energy and power grids, and beyond. Automated verification and policy synthesis for stochastic hybrid systems can be inherently challenging: this is due to the heterogeneity of their dynamics (presence of continuous and discrete components), the presence of uncertainty, and in some applications the large dimension of state and input sets. Over the past few years, a few hundred articles have investigated these models, and developed diverse and powerful approaches to mitigate difficulties encountered in the analysis and synthesis of such complex stochastic systems. In this survey, we overview the most recent results in the literature and discuss different approaches, including (in)finite abstractions, verification and synthesis for temporal logic specifications, stochastic similarity relations, (control) barrier certificates, compositional techniques, and a selection of results on continuous-time stochastic systems; we finally survey recently developed software tools that implement the discussed approaches. Throughout the manuscript we discuss a few open topics to be considered as potential future research directions: we hope that this survey will guide younger researchers through a comprehensive understanding of the various challenges, tools, and solutions in this enticing and rich scientific area.