A survey on compositional algorithms for verification and synthesis in supervisory control

This survey gives an overview of the current research on compositional algorithms for verification and synthesis of modular systems modelled as interacting finite-state machines. Compositional algorithms operate by repeatedly simplifying individual components of a large system, replacing them by smaller so-called abstractions, while preserving critical properties. In this way, the exponential growth of the state space can be limited, making it possible to analyse much bigger state spaces than possible by standard state space exploration. This paper gives an introduction to the principles underlying compositional methods, followed by a survey of algorithmic solutions from the recent literature that use compositional methods to analyse systems automatically. The focus is on applications in supervisory control of discrete event systems, particularly on methods that verify critical properties or synthesise controllable and nonblocking supervisors

Exploration policies for on-the-fly controller synthesis: a reinforcement learning approach

Controller synthesis is in essence a case of model-based planning for non-deterministic environments in which plans (actually “strategies”) are meant to preserve system goals indefinitely. In the case of supervisory control environments are specified as the parallel composition of state machines and valid strategies are required to be “non-blocking” (i.e., always enabling the environment to reach certain marked states) in addition to safe (i.e., keep the system within a safe zone). Recently, On-the-fly Directed Controller Synthesis techniques were proposed to avoid the exploration of the entire -and exponentially large- environment space, at the cost of non-maximal permissiveness, to either find a strategy or conclude that there is none. The incremental exploration of the plant is currently guided by a domain-independent human-designed heuristic. In this work, we propose a new method for obtaining heuristics based on Reinforcement Learning (RL). The synthesis algorithm is thus framed as an RL task with an unbounded action space and a modified version of DQN is used. With a simple and general set of features that abstracts both states and actions, we show that it is possible to learn heuristics on small versions of a problem that generalize to the larger instances, effectively doing zero-shot policy transfer. Our agents learn from scratch in a highly partially observable RL task and outperform the existing heuristic overall, in instances unseen during training

A Forward On-The-Fly Approach for Safety and Reachability Controller Synthesis of Timed Systems

RÉSUMÉ Cette thèse s’intéresse à la synthèse de contrôleurs pour des systèmes temps réel (systèmes temporisés). Partant d’un système temps réel modélisé par un réseau de Petri temporel composé de transitions contrôlables et non contrôlables (TPN), le contrôle vise à forcer, en restreignant les intervalles de franchissement des transitions contrôlables, le système à satisfaire les propriétés souhaitées. Nous proposons, dans cette thèse, un algorithme pour synthétiser de tels contrôleurs pour des propriétés de sûreté et d’accessibilité. Cet algorithme, basé sur la méthode de graphe de classes d’états, calcule à la volée les classes d’états atteignables du TPN tout en collectant progressivement les sous-intervalles de tir à éviter, afin de satisfaire les propriétés souhaitées. Avec cet algorithme, il n’est plus nécessaire de calculer les prédécesseurs contrôlables et de partitionner récursivement les classes d’états jusqu’à atteindre un point fixe, comme c’est le cas dans les autres approches basées sur l’exploration, en avant et en arrière, de l’espace des états du système. Nous prouvons formellement la correction de l’algorithme, puis nous montrons que dans la catégorie des contrôleurs basés sur la restriction des intervalles de tir, l’algorithme, proposé dans cette thèse, synthétise un contrôleur optimal (le plus permissif possible). Afin d’atténuer davantage le problème d’explosion combinatoire, nous montrons comment combiner cette approche avec une abstraction par l’inclusion, par union-convexe ou par enveloppe-convexe. Nous montrons également comment exploiter cet algorithme pour générer des contrôleurs décentralisés. Enfin, nous proposons d’appliquer cet algorithme pour contrôler des TPN par des chronomètres. Notre algorithme permet de partitionner les intervalles des transitions en “bons” et “mauvais” sous-intervalles (à éviter). L’idée est d’utiliser des chronomètres pour suspendre les tâches (transitions) durant leurs mauvais sous-intervalles et les activer dans leurs “bons sous-intervalles”. Il s’agit donc de contrôler les réseaux de Petri temporels en associant des chronomètres aux transitions contrôlables, pour obtenir ainsi des réseaux de Petri temporels contrôlés.----------ABSTRACT This thesis deals with controller synthesis for real time systems (timed systems). Given a real time system modeled as a Time Petri Net (TPN) with controllable and uncontrollable transitions, the control aims at forcing the system to satisfy properties of interest, by limiting the firing intervals of controllable transitions. We propose, in this thesis, an algorithm to synthesize such controllers for safety / reachability properties. This algorithm, based on the state class graph method, computes on-the-fly the reachable state classes of the TPN while collecting progressively firing subintervals to be avoided so that the property is satisfied. It does not need to compute controllable predecessors and then split state classes until reaching a fixpoint, as it is the case for other approaches based on backward and forward exploration of state space of the system. We prove formally the correctness of the algorithm and show that, in the category of state dependent controllers based on the restriction of firing intervals, the algorithm proposed in this thesis, synthesizes maximally permissive controllers. In order to attenuate the state explosion problem, we show how to combine efficiently this approach with an abstraction by inclusion, convex union or convex hull. Afterwards, we discuss the compatibility of this method with distributed systems and decentralized controllers. Finally, we apply this algorithm to control TPN with controllable and uncontrollable transitions by stopwatch. In this approach, we find the subintervals violating the given properties and our objective is to suspend the tasks (transitions) during their bad subintervals and to resume them later. The controller is synthesized through the same algorithm already introduced. In this approach, we suggest to control time Petri nets by associating stopwatches to controllable transitions and to achieve a controlled time Petri nets

Principles of Security and Trust

This open access book constitutes the proceedings of the 8th International Conference on Principles of Security and Trust, POST 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 10 papers presented in this volume were carefully reviewed and selected from 27 submissions. They deal with theoretical and foundational aspects of security and trust, including on new theoretical results, practical applications of existing foundational ideas, and innovative approaches stimulated by pressing practical problems

Formal Techniques for Component-based Design of Embedded Systems

Embedded systems have become ubiquitous - from avionics and automotive over consumer electronics to medical devices. Failures may entailmaterial damage or compromise safety of human beings. At the same time, shorter product cycles, together with fast growing complexity of the systems to be designed, create a tremendous need for rigorous design techniques. The goal of component-based construction is to build complex systems from simpler components that are well understood and can be (re)used so as to accelerate the design process. This document presents a summary of the formal techniques for component-based design of embedded systems I have (co-)developed

Contagion à effet de seuil dans les réseaux complexes

Networks arise frequently in the study of complex systems, since interactions among the components of such systems are critical. Networks can act as a substrate for dynamical process, such as the diffusion of information or disease throughout populations. Network structure can determine the temporal evolution of a dynamical process, including the characteristics of the steady state.The simplest representation of a complex system is an undirected, unweighted, single layer graph. In contrast, real systems exhibit heterogeneity of interaction strength and type. Such systems are frequently represented as weighted multiplex networks, and in this work we incorporate these heterogeneities into a master equation formalism in order to study their effects on spreading processes. We also carry out simulations on synthetic and empirical networks, and show that spreading dynamics, in particular the speed at which contagion spreads via threshold mechanisms, depend non-trivially on these heterogeneities. Further, we show that an important family of networks undergo reentrant phase transitions in the size and frequency of global cascades as a result of these interactions.A challenging feature of real systems is their tendency to evolve over time, since the changing structure of the underlying network is critical to the behaviour of overlying dynamical processes. We show that one aspect of temporality, the observed “burstiness” in interaction patterns, leads to non-monotic changes in the spreading time of threshold driven contagion processes.The above results shed light on the effects of various network heterogeneities, with respect to dynamical processes that evolve on these networks.Les interactions entre les composants des systèmes complexes font émerger différents types de réseaux. Ces réseaux peuvent jouer le rôle d’un substrat pour des processus dynamiques tels que la diffusion d’informations ou de maladies dans des populations. Les structures de ces réseaux déterminent l’évolution d’un processus dynamique, en particulier son régime transitoire, mais aussi les caractéristiques du régime permanent.Les systèmes complexes réels manifestent des intéractions hétérogènes en type et en intensité. Ces systèmes sont représetés comme des réseaux pondérés à plusieurs couches. Dans cette thèse, nous développons une équation maîtresse afin d’intégrer ces hétérogénéités et d’étudier leurs effets sur les processus de diffusion. À l’aide de simulations mettant en jeu des réseaux réels et générés, nous montrons que les dynamiques de diffusion sont liées de manière non triviale à l’hétérogénéité de ces réseaux, en particulier la vitesse de propagation d’une contagion basée sur un effet de seuil. De plus, nous montrons que certaines classes de réseaux sont soumises à des transitions de phase réentrantes fonctions de la taille des “global cascades”.La tendance des réseaux réels à évoluer dans le temps rend difficile la modélisation des processus de diffusion. Nous montrons enfin que la durée de diffusion d’un processus de contagion basé sur un effet de seuil change de manière non-monotone du fait de la présence de“rafales” dans les motifs d’intéractions. L’ensemble de ces résultats mettent en lumière les effets de l’hétérogénéité des réseaux vis-à-vis des processus dynamiques y évoluant