Robustness-guided temporal logic testing and verification for Stochastic Cyber-Physical Systems

Abstract

We present a framework for automatic specificationguided testing for Stochastic Cyber-Physical Systems (SCPS). The framework utilizes the theory of robustness of Metric Temporal Logic (MTL) specifications to quantify how robustly an SCPS satisfies a specification in MTL. The goal of the testing framework is to detect system operating conditions that cause the system to exhibit the worst expected specification robustness. The resulting expected robustness minimization problem is solved using Markov chain Monte Carlo algorithms. This also allows us to use finite-time guarantees, which quantify the quality of the solution after a finite number of simulations. In a Model-Based Design (MBD) process, our framework can be combined with Statistical Model Checking (SMC). Finally, we present a case study on a high fidelity engine model where the goal is to verify the air-to-fuel ratio problem.

SpaTeL

“…The temporal version of problem 2 has been solved in [1,26].We study the spatio-temporal case in this paper. Problem 2 can be formulated as an optimization problem:…”

“…Now, we define the QTS max distance, a measure of similarity of two given QTSs. (1) , L (1) ) and Q (2) = (A (2) , a (2) 0 , τ (2) , Σ, [.] (2) , L (2) ) is defined as:…”

Model Aspects of Quality of Service Management in Machine to Machine Communications

“…OMA DiagMon Trap Events specification defines a number of standardized traps [14]. Geographic trap goes to active when a device enters into a specific geographic area.…”

“…The behavior of the QoS Management Agent is described by temporal logic [14]. We use a minimal set of standard notations G for always, U for until, and N for next.…”

Efficient Parametric Identification for STL

“…This problem, dual of verification, attempts not to prove that the system M is correct under all inputs u ∈ U , but simply to find a faulty execution w = M(u), without any formal guarantees that it will be found. The most effective technique, as illustrated in [2,34], turns the falsification problem into the following optimization problem: "minimize ρ(φ, w) subject to w = M(u), u ∈ U ." The robustness value ρ is expected to be continuous in u, and by definition is w ̸ |= φ when ρ(φ, w) < 0.…”