Dans cette thèse, nous nous intéressons à la problématique de la vérification formelle des systèmes critiques temps réel, c’est-à-dire des systèmes dont l’exécution dépend de certaines contraintes temporelles. La spécification formelle des exigences pour de tels systèmes, ainsi que leur vérification, reste une tâche très compliquée, surtout pour les non experts. Plusieurs solutions ont été proposées pour faciliter la spécification et la vérification des systèmes temps-réels. Un premier type d’approche est basée sur la définition d’un ensemble de patrons de spécification qui représentent les propriétés les plus utilisées en pratique. Cependant, ce type de solutions n’est pas toujours supporté par un outillage de vérification efficace, dans le sens que les auteurs de ces langages de patrons ne fournissent pas directement une implantation pour leur langage. Un second type d’approches repose sur l’utilisation du formalisme des logiques temporelles pour spécifier les propriétés à vérifier et sur les techniques de model-checking pour leur vérification. S’agissant de systèmes temps-réels, il est dans ce cas nécessaire d’utiliser des extensions temporisées des logiques temporelles. Cependant, ces approches donnent le plus souvent lieu à des problèmes de model-checking qui sont indécidable, ou dont la complexité en pratique est très élevée. Dans ce travail, nous suivons la première approche et proposons un langage de patrons de propriétés temps-réels accompagnés d’un outil de vérification par model- checking. Nous apportons plusieurs contributions à ce domaine. Nous proposons un cadre théorique complet pour la spécification et la vérification de patrons de propriétés temps réel. Notre approche a été implantée dans le contexte du langage de modélisation Fiacre. Enfin, nous définissons deux méthodes complémentaires permettant de vérifier la correction de notre approche de vérification / The formal verification of critical, reactive systems is a very complicated task, especially for non experts. In this work, we more particularly address the problem of real time systems, that is in the situation where the correctness of the system depends upon timing constraints, such as the “timeliness” of some interactions. Many solutions have been proposed to ease the specification and the verification of such systems. An interesting approach—that we follow in this thesis—is based on the definition of specification patterns, that is sets of general, reusable templates for commonly occurring classes of properties. However, patterns are rarely implemented, in the sense that the designers of specification languages rarely provide an effective verification method for checking a pattern on a system. The most common technique is to rely on a timed extension of a temporal logic to define the semantics of patterns and then to use a model-checker for this logic. However, this approach may be inadequate, in particular if patterns require the use of a logic associated to an undecidable model-checking problem or to an algorithm with a very high practical complexity. We make several contributions. We propose a complete theoretical framework to specify and check real time properties on the formal model of a system. First, our framework provides a set of real time specification patterns. We provide a verification technique based on the use of observers that has been implemented in a tool for the Fiacre modelling language. Finally, we provide two methods to check the correctness of our verification approach; a “semantics”—theoretical— method as well as a “graphical”-practical- method

This thesis deals with the application of bounded model checking method for self-healing assurance of concurrency related problems. The self-healing is currently interested in the Java programming language. Therefore, it concetrate mainly on the model checker Java PathFinder which is built for handling Java programs. The verification method is implemented like the Record&Replay trace strategy for navigation through a state space and performance bounded model checking from reached state through the use of Record&Replay trace strategy. Java PathFinder was extended by new moduls and interfaces in order to perform the bounded model checking for self-healing assurance. Bounded model checking is applied at the neighbourhood of self-healing.

Bit flips are known to be a source of strange system behavior, failures, and crashes. They can cause dramatic financial loss, security breaches, or even harm human life. Caused by energized particles arising from, e.g., cosmic rays or heat, they are hardly avoidable. Due to transistor sizes becoming smaller and smaller, modern hardware becomes more and more prone to bit flips. This yields a high scientific interest, and many techniques to make systems more resilient against bit flips are developed. Fault-tolerance techniques are techniques that detect and react to bit flips or their effects. Before using these techniques, they typically need to be configured for the particular system they shall protect, the grade of resilience that shall be achieved, and the environment. State-of-the-art configuration approaches have a high risk of being imprecise, of being affected by undesired side effects, and of yielding questionable resilience measures. In this thesis we encourage the usage of formal methods for resiliency configuration, point out advantages and investigate difficulties. We exemplarily investigate two systems that are equipped with fault-tolerance techniques, and we apply parametric variants of probabilistic model checking to obtain optimal configurations for pre-defined resilience criteria. Probabilistic model checking is an automated formal method that operates on Markov models, i.e., state-based models with probabilistic transitions, where costs or rewards can be assigned to states and transitions. Probabilistic model checking can be used to compute, e.g., the probability of having a failure, the conditional probability of detecting an error in case of bit-flip occurrence, or the overhead that arises due to error detection and correction. Parametric variants of probabilistic model checking allow parameters in the transition probabilities and in the costs and rewards. Instead of computing values for probabilities and overhead, parametric variants compute rational functions. These functions can then be analyzed for optimality. The considered fault-tolerant systems are inspired by the work of project partners. The first system is an inter-process communication protocol as it is used in the Fiasco.OC microkernel. The communication structures provided by the kernel are protected against bit flips by a fault-tolerance technique. The second system is inspired by the redo-based fault-tolerance technique \haft. This technique protects an application against bit flips by partitioning the application's instruction flow into transaction, adding redundance, and redoing single transactions in case of error detection. Driven by these examples, we study challenges when using probabilistic model checking for fault-tolerance configuration and present solutions. We show that small transition probabilities, as they arise in error models, can be a cause of previously known accuracy issues, when using numeric solver in probabilistic model checking. We argue that the use of non-iterative methods is an acceptable alternative. We debate on the usability of the rational functions for finding optimal configurations, and show that for relatively short rational functions the usage of mathematical methods is appropriate. The redo-based fault-tolerance model suffers from the well-known state-explosion problem. We present a new technique, counter-based factorization, that tackles this problem for system models that do not scale because of a counter, as it is the case for this fault-tolerance model. This technique utilizes the chain-like structure that arises from the counter, splits the model into several parts, and computes local characteristics (in terms of rational functions) for these parts. These local characteristics can then be combined to retrieve global resiliency and overhead measures. The rational functions retrieved for the redo-based fault-tolerance model are huge - for small model instances they already have the size of more than one gigabyte. We therefor can not apply precise mathematic methods to these functions. Instead, we use the short, matrix-based representation, that arises from factorization, to point-wise evaluate the functions. Using this approach, we systematically explore the design space of the redo-based fault-tolerance model and retrieve sweet-spot configurations.

Probabilistic model checking is a powerful technique used to ensure the correct functioning of systems which exhibit real-time and stochastic behaviours. Many such systems are embedded and used in safety-critical situations, to mention implantable medical devices. This thesis aims to develop a formal model-based framework that is tailored for the analysis and verification of cardiac pacemakers. The contributions are novel approaches for the automatic verification and validation of real-time properties over continuous-time models, which are applicable to software embedded in medical devices. First, we address the problem of model checking continuous-time Markov chain (CTMC) models against real-time specifications given in the form of temporal logic, namely, metric temporal logic (MTL) and linear duration properties (LDP), or as timed automata (TA). The main question that we address is “given a continuous-time Markov chain, what is the probability of the set of timed paths that satisfy the real-time property under consideration?”. We provide novel algorithms to approximate the probability through generating systems of linear inequalities over variables that represent the waiting times in system states, and then solving multidimensional integrals over this set. Second, we present a model-based framework to support the design and verification of pacemakers against real-time properties. The pacemaker is modelled as a network of timed automata, whereas the human heart is modelled either as a network of timed automata or as a network of hybrid automata. Our framework can be instantiated with personalised heart models whose parameters can be learnt from patient data, and we have done so to validate our approach. We introduce property patterns and the counting metric temporal logic (CMTL) in order to specify the properties of interest. We provide new verification algorithms for networks of timed or hybrid automata against property patterns and CMTL. Finally, we pose and solve the parameter synthesis problem, i.e., given a network of timed automata containing model parameters, an objective function and a CMTL formula, find the set of parameter valuations, whenever existing, which satisfy the CMTL formula and maximise the objective function. The framework has been implemented using Simulink, Matlab and Python code. Extensive experimental results on pacemaker models have been carried out and discussed in detail. The techniques developed in this thesis can assist in the design and verification of software embedded in medical devices.

The software architecture of a system is often used to guide and constrain its implementation. While the code structure of an initial implementation is likely to conform to its intended architecture, its dynamic properties cannot always be fully checked until deployment. Routine maintenance and changing requirements can also lead to a deployed system deviating from this architecture over time. Dynamic architecture conformance checking plays an important part in ensuring that software architectures and corresponding implementations stay consistent with one another throughout the software lifecycle. However, runtime conformance checking strategies often force changes to the software, demand tight coupling between the monitoring framework and application, impact performance, require manual intervention, and lack flexibility and extensibility, affecting their viability in practice. This thesis presents a dynamic conformance checking framework called PANDArch framework, which aims to address these issues. PANDArch is designed to be automated, pluggable, non-intrusive, performance-centric, extensible and tolerant of incomplete specifications. The thesis describes the concept and design principles behind PANDArch, and its current implementation, which uses an architecture description language to specify architectures and Java as the target language. The framework is evaluated using three open source software products of different types. The results suggest that dynamic architectural conformance checking with the proposed features may be a viable option in practice.

<p>Our media is saturated with claims of ``facts'' made from data. Database research has in the past focused on how to answer queries, but has not devoted much attention to discerning more subtle qualities of the resulting claims, e.g., is a claim ``cherry-picking''? This paper proposes a Query Response Surface (QRS) based framework that models claims based on structured data as parameterized queries. A key insight is that we can learn a lot about a claim by perturbing its parameters and seeing how its conclusion changes. This framework lets us formulate and tackle practical fact-checking tasks --- reverse-engineering vague claims, and countering questionable claims --- as computational problems. Within the QRS based framework, we take one step further, and propose a problem along with efficient algorithms for finding high-quality claims of a given form from data, i.e. raising good questions, in the first place. This is achieved to using a limited number of high-valued claims to represent high-valued regions of the QRS. Besides the general purpose high-quality claim finding problem, lead-finding can be tailored towards specific claim quality measures, also defined within the QRS framework. An example of uniqueness-based lead-finding is presented for ``one-of-the-few'' claims, landing in interpretable high-quality claims, and an adjustable mechanism for ranking objects, e.g. NBA players, based on what claims can be made for them. Finally, we study the use of visualization as a powerful way of conveying results of a large number of claims. An efficient two stage sampling algorithm is proposed for generating input of 2d scatter plot with heatmap, evalutaing a limited amount of data, while preserving the two essential visual features, namely outliers and clusters. For all the problems, we present real-world examples and experiments that demonstrate the power of our model, efficiency of our algorithms, and usefulness of their results.</p> / Dissertation

<p align="justify">Computer Science is currently facing a grand challenge : finding good design practices for embedded systems. Embedded systems are essentially computers interacting with some physical process. You could find one in a braking systems or in a nuclear power plant for example. They present several design difficulties : first they are reactive systems, interacting indefinitely with their environment. Second,they must satisfy real-time constraints specifying when they should respond, and not only how. Finally, their environment is often deeply continuous, presenting complex dynamics. The formal models of choice for specifying such systems are timed and hybrid automata for which model checking is pretty well studied.</p> <p align="justify">In a first part of this thesis, we study a complete design approach, including verification and code generation, for timed automata. We have to define a new semantics for timed automata, the AASAP semantics, that preserves the decidability properties for model checking and at the same time is implementable. Our notion of implementability is completely novel, and relies on the simulation of a semantics that is obviously implementable on a real platform. We wrote tools for the analysis and code generation and exemplify them on a case study about the well known Philips Audio Control Protocol.</p> <p align="justify">In a second part of this thesis, we study the problem of controller synthesis for an environment specified as a hybrid automaton. We give a new solution for discrete controllers having only an imperfect information about the state of the system. In the process, we defined a new algorithm, based on the monotonicity of the controllable predecessors operator, for efficiently finding a controller and we show some promising applications on a classical problem : the universality test for finite automata.

Model checking is a fully-automatic formal verification method that has been extremely successful in validating and verifying safety-critical systems in the past three decades. In the past fifteen years, there has been a lot of work in extending many model checking algorithms over finite-state systems to finitely representable infinitestate systems. Unlike in the case of finite systems, decidability can easily become a problem in the case of infinite-state model checking. In this thesis, we present generic and specific techniques that can be used to derive decidability with near-optimal computational complexity for various model checking problems over infinite-state systems. Generic techniques and specific techniques primarily differ in the way in which a decidability result is derived. Generic techniques is a “top-down” approach wherein we start with a Turing-powerful formalismfor infinitestate systems (in the sense of being able to generate the computation graphs of Turing machines up to isomorphisms), and then impose semantic restrictions whereby the desired model checking problem becomes decidable. In other words, to show that a subclass of the infinite-state systems that is generated by this formalism is decidable with respect to the model checking problem under consideration, we will simply have to prove that this subclass satisfies the semantic restriction. On the other hand, specific techniques is a “bottom-up” approach in the sense that we restrict to a non-Turing powerful formalism of infinite-state systems at the outset. The main benefit of generic techniques is that they can be used as algorithmic metatheorems, i.e., they can give unified proofs of decidability of various model checking problems over infinite-state systems. Specific techniques are more flexible in the sense they can be used to derive decidability or optimal complexity when generic techniques fail. In the first part of the thesis, we adopt word/tree automatic transition systems as a generic formalism of infinite-state systems. Such formalisms can be used to generate many interesting classes of infinite-state systems that have been considered in the literature, e.g., the computation graphs of counter systems, Turing machines, pushdown systems, prefix-recognizable systems, regular ground-tree rewrite systems, PAprocesses, order-2 collapsible pushdown systems. Although the generality of these formalisms make most interesting model checking problems (even safety) undecidable, they are known to have nice closure and algorithmic properties. We use these nice properties to obtain several algorithmic metatheorems over word/tree automatic systems, e.g., for deriving decidability of various model checking problems including recurrent reachability, and Linear Temporal Logic (LTL) with complex fairness constraints. These algorithmic metatheorems can be used to uniformly prove decidability with optimal (or near-optimal) complexity of various model checking problems over many classes of infinite-state systems that have been considered in the literature. In fact, many of these decidability/complexity results were not previously known in the literature. In the second part of the thesis, we study various model checking problems over subclasses of counter systems that were already known to be decidable. In particular, we consider reversal-bounded counter systems (and their extensions with discrete clocks), one-counter processes, and networks of one-counter processes. We shall derive optimal complexity of various model checking problems including: model checking LTL, EF-logic, and first-order logic with reachability relations (and restrictions thereof). In most cases, we obtain a single/double exponential reduction in the previously known upper bounds on the complexity of the problems.

Cette thèse propose une nouvelle approche pour la synthèse de valeurs temporelles dans les systèmes temporisés. Notre approche est basée sur la méthode inverse suivante : à partir d’une instance de référence des paramètres, nous synthétisons une contrainte sur les paramètres, garantissant le même comportement que pour l’instance de référence, abstraction faite du temps. Il en résulte un critère de robustesse pour le système. En itérant cette méthode sur des points dans un domaine paramétrique borné, nous sommes alors à même de partitionner l’espace des paramètres en bonnes et mauvaises zones par rapport à une propriété à vérifier. Ceci nous donne une cartographie comportementale du système. Cette méthode s’étend aisément aux systèmes probabilistes. Nous présentons également des variantes de la méthode inverse pour les graphes orientés valués et les processus de décision markoviens. Parmi les prototypes implémentés, IMITATOR II implémente la méthode inverse et la cartographie pour les automates temporisés. Ce prototype nous a permis de synthétiser de bonnes valeurs pour les paramètres temporels de plusieurs études de cas, dont un modèle abstrait d’une mémoire commercialisée par le fabricant de puces STMicroelectronics, ainsi que plusieurs protocoles de communication. / This thesis proposes a novel approach for the synthesis of delays for timed systems, in particular in the framework oftimed automata, a model for verifying real-time systems. Our approach relies on the following inverse method: given a reference valuation of the parameters, we synthesize a constraint on the parameters, guaranteeing the same timeabstract linear behavior as for the reference valuation. This gives a criterion of robustness to the system. By iterating this inverse method on various points of a bounded parameter domain, we are then able to partition the parametric space into good and bad zones, with respect to a given property one wants to verify. This gives a behavioral cartography of the system. This method extended to probabilistic systems allows to preserve minimum and maximum probabilities of reachability properties. We also present variants of the inverse method for directed weighted graphs and Markov Decision Processes. Several prototypes have been implemented; in particular, IMITATOR II implements the inverse method and the cartography for timed automata. It allowed us to synthesize parameter values for several case studies such as an abstract model of a memory circuit sold by the chipset manufacturer ST-Microelectronics, and various communication protocols.

Software-intensive systems are increasingly expected to operate under changing and uncertain conditions, including not only varying user needs and workloads, but also fluctuating resource capacity. Self-adaptation is an approach that aims to address this problem, giving systems the ability to change their behavior and structure to adapt to changes in themselves and their operating environment without human intervention. Self-adaptive systems tend to be reactive and myopic, adapting in response to changes without anticipating what the subsequent adaptation needs will be. Adapting reactively can result in inefficiencies due to the system performing a suboptimal sequence of adaptations. Furthermore, some adaptation tactics—atomic adaptation actions that leave the system in a consistent state—have latency and take some time to produce their effect. In that case, reactive adaptation causes the system to lag behind environment changes. What is worse, a long running adaptation action may prevent the system from performing other adaptations until it completes, further limiting its ability to effectively deal with the environment changes. To address these limitations and improve the effectiveness of self-adaptation, we present proactive latency-aware adaptation, an approach that considers the timing of adaptation (i) leveraging predictions of the near future state of the environment to adapt proactively; (ii) considering the latency of adaptation tactics when deciding how to adapt; and (iii) executing tactics concurrently. We have developed three different solution approaches embodying these principles. One is based on probabilistic model checking, making it inherently able to deal with the stochastic behavior of the environment, and guaranteeing optimal adaptation choices over a finite decision horizon. The second approach uses stochastic dynamic programming to make adaptation decisions, and thanks to performing part of the computations required to make those decisions off-line, it achieves a speedup of an order of magnitude over the first solution approach without compromising optimality. A third solution approach makes adaptation decisions based on repertoires of adaptation strategies— predefined compositions of adaptation tactics. This approach is more scalable than the other two because the solution space is smaller, allowing an adaptive system to reap some of the benefits of proactive latency-aware adaptation even if the number of ways in which it could adapt is too large for the other approaches to consider all these possibilities. We evaluate the approach using two different classes of systems with different adaptation goals, and different repertoires of adaptation strategies. One of them is a web system, with the adaptation goal of utility maximization. The other is a cyberphysical system operating in a hostile environment. In that system, self-adaptation must not only maximize the reward gained, but also keep the probability of surviving a mission above a threshold. In both cases, our results show that proactive latency-aware adaptation improves the effectiveness of self-adaptation with respect to reactive time-agnostic adaptation.