Benoît Barbot

HASL: A new approach for performance evaluation and model checking from concepts to experimentation

We introduce the Hybrid Automata Stochastic Language (HASL), a new temporal logic formalism for the verification of Discrete Event Stochastic Processes (DESP). HASL employs a Linear Hybrid Automaton (LHA) to select prefixes of relevant execution paths of a DESP. LHA allows rather elaborate information to be collected on-the-fly during path selection, providing the user with powerful means to express sophisticated measures. A formula of HASL consists of an LHA and an expression Z referring to moments of path random variables. A simulation-based statistical engine is employed to obtain a confidence interval estimate of the expected value of Z. In essence, HASL provides a unifying verification framework where temporal reasoning is naturally blended with elaborate reward-based analysis. Moreover, we have implemented a tool, named COSMOS, for performing analysis of HASL formula for DESP modelled by Petri nets. Using this tool we have developed two detailed case studies: a flexible manufacturing system and a genetic oscillator.

Estimation and Verification of Hybrid Heart Models for Personalised Medical and Wearable Devices

We are witnessing a huge growth in popularity of wearable and implantable devices equipped with sensors that are capable of monitoring a range of physiological processes and communicating the data to smartphones or to medical monitoring devices. Applications include not only medical diagnosis and treatment, but also biometric identification and authentication systems. An important requirement is personalisation of the devices, namely, their ability to adapt to the physiology of the human wearer and to faithfully reproduce the characteristics in real-time for the purposes of authentication or optimisation of medical therapies. In view of the complexity of the embedded software that controls such devices, model-based frameworks have been advocated for their design, development, verification and testing. In this paper, we focus on applications that exploit the unique characteristics of the heart rhythm. We introduce a hybrid automata model of the electrical conduction system of a human heart, adapted from Lian et al. [8], and present a framework for the estimation of personalised parameters, including the generation of synthetic ECGs from the model. We demonstrate the usefulness of the framework on two applications, ensuring safety of a pacemaker against a personalised heart model and ECG-based user authentication.

On Quantitative Modelling and Verification of DNA Walker Circuits Using Stochastic Petri Nets

Molecular programming is an emerging field concerned with building synthetic biomolecular computing devices at the nanoscale, for example from DNA or RNA molecules. Many promising applications have been proposed, ranging from diagnostic biosensors and nanorobots to synthetic biology, but prohibitive complexity and imprecision of experimental observations makes reliability of molecular programs difficult to achieve. This paper advocates the development of design automation methodologies for molecular programming, highlighting the role of quantitative verification in this context. We focus on DNA ‘walker’ circuits, in which molecules can be programmed to traverse tracks placed on a DNA origami tile, taking appropriate decisions at junctions and reporting the outcome when reaching the end of the track. The behaviour of molecular walkers is inherently probabilistic and thus probabilistic model checking methods are needed for their analysis. We demonstrate how DNA walkers can be modelled using stochastic Petri nets, and apply statistical model checking using the tool Cosmos to analyse the reliability and performance characteristics of the designs. The results are compared and contrasted with those obtained for the PRISM model checker. The paper ends by summarising future research challenges in the field.

Building Power Consumption Models from Executable Timed I/O Automata Specifications

We develop a novel model-based hardware-in-the-loop (HIL) framework for optimising energy consumption of embedded software controllers. Controller and plant models are specified as networks of parameterised timed input/output automata and translated into executable code. The controller is encoded into the target embedded hardware, which is connected to a power monitor and interacts with the simulation of the plant model. The framework then generates a power consumption model that maps controller transitions to distributions over power measurements, and is used to optimise the timing parameters of the controller, without compromising a given safety requirement. The novelty of our approach is that we measure the real power consumption of the controller and use thus obtained data for energy optimisation. We employ timed Petri nets as an intermediate representation of the executable specification, which facilitates efficient code generation and fast simulations. Our framework uniquely combines the advantages of rigorous specifications with accurate power measurements and methods for online model estimation, thus enabling automated design of correct and energy-efficient controllers.

A Modular Approach for Reusing Formalisms in Verification Tools of Concurrent Systems

Over the past two decades, numerous verification tools have been successfully used for verifying complex concurrent systems, modelled using various formalisms. However, it is still hard to coordinate these tools since they rely on such a large number of formalisms. Having a proper syntactical mechanism to interrelate them through variability would increase the capability of effective integrated formal methods. In this paper, we propose a modular approach for defining new formalisms by reusing existing ones and adding new features and/or constraints. Our approach relies on standard XML technologies; their use provides the capability of rapidly and automatically obtaining tools for representing and validating models. It thus enables fast iterations in developing and testing complex formalisms. As a case study, we applied our modular definition approach on families of Petri nets and timed automata.

Uniform Sampling for Timed Automata with Application to Language Inclusion Measurement

Monte Carlo model checking introduced by Smolka and Grosu is an approach to analyse non-probabilistic models using sampling and draw conclusions with a given confidence interval by applying statistical inference. Though not exhaustive, the method enables verification of complex models, even in cases where the underlying problem is undecidable. In this paper we develop Monte Carlo model checking techniques to evaluate quantitative properties of timed languages. Our approach is based on uniform random sampling of behaviours, as opposed to isotropic sampling that chooses the next step uniformly at random. The uniformity is defined with respect to volume measure of timed languages previously studied by Asarin, Basset and Degorre. We improve over their work by employing a zone graph abstraction instead of the region graph abstraction and incorporating uniform sampling within a zone-based Monte Carlo model checking framework. We implement our algorithms using tools PRISM, SageMath and COSMOS, and demonstrate their usefulness on statistical language inclusion measurement in terms of volume.