A Retrospective Look at the Monitoring and Checking (MaC) Framework

The Monitoring and Checking (MaC) project gave rise to a framework for runtime monitoring with respect to formally specified properties, which later came to be known as runtime verification. The project also built a pioneering runtime verification tool, Java-MaC, that was an instantiation of the approach to check properties of Java programs. In this retrospective, we discuss decisions made in the design of the framework and summarize lessons learned in the course of the project

Towards interpreting recurrent neural networks through probabilistic abstraction

National Research Foundation (NRF) Singapore under its AI Singapore Programm

Runtime Verification with State Estimation

Abstract. We introduce the concept of Runtime Verification with State Estimation and show how this concept can be applied to estimate the probability that a temporal property is satisfied by a run of a program when monitoring overhead is reduced by sampling. In such situations, there may be gaps in the observed program executions, thus making accurate estimation challenging. To deal with the effects of sampling on runtime verification, we view event sequences as observation sequences of a Hidden Markov Model (HMM), use an HMM model of the monitored program to “fill in ” sampling-induced gaps in observation sequences, and extend the classic forward algorithm for HMM state estimation (determine the probability of a state sequence, given an observation sequence) to compute the probability that the property is satisfied by an execution of the program. To validate our approach, we present a case study based on the mission software for a Mars rover. The results of our case study demonstrate high prediction accuracy for the probabilities computed by our algorithm. They also show that our technique is much more accurate than simply evaluating the temporal property on the given observation sequences, ignoring the gaps.

Temporal Monitors for TinyOS

Abstract. Networked embedded systems generally have extremely low visibility of system faults. In this paper, we report on experimenting with online, node-local temporal monitors for networked embedded nodes running the TinyOS operating system and programmed in the nesC language. We instrument the original node software to signal asynchronous atomic events to a local nesC component running a runtime verification algorithm; this checks LTL properties automatically translated into deterministic state-machine monitors and encoded in nesC. We focus on quantifying the added (i) memory and (ii) computational overhead of this embedded checker and identify practical upper bounds with runtime checking on mainstream embedded platforms