Within the context of the verification of infinite-state systems, 'Regular model checking' is the name of a family of techniques in which states are represented by words or trees, sets of states by finite automata on these objects, and transitions by finite automata operating on pairs of state encodings, i.e. finite-state transducers. In this context, the problem of computing the set of reachable states of a system can be reduced to the one of computing the iterative closure of the finite-state transducer representing its transition relation. This thesis provides several techniques to computing the transitive closure of a finite-state transducer. One of the motivations of the thesis is to show the feasibility and usefulness of this approach through a combination of the necessary theoretical developments, implementation, and experimentation. For systems whose states are encoded by words, the iteration technique proceeds by comparing a finite sequence of successive powers of the transducer, detecting an 'increment' that is added to move from one power to the next, and extrapolating the sequence by allowing arbitrary repetitions of this increment. For systems whose states are represented by trees, the iteration technique proceeds by computing the powers of the transducer and progressively collapsing their states according to an equivalence relation until a fixed point is reached. The proposed iteration techniques can just as well be exploited to compute the closure of a given set of states by repeated applications of the transducer, which has proven to be a very effective way of using the technique. Various examples have been handled completely within the automata-theoretic setting. Another applications of the techniques are the verification of linear temporal properties as well as the computation of the convex hull of a finite set of integer vectors.

Reliable operation of every day use computing system, from simple coffee machines to complex flight controller system in an aircraft, is necessary to save time, money, and in some cases lives. System testing can check for the presence of unwanted execution but cannot guarantee the absence of such. Probabilistic model checking techniques have demonstrated significant potential in verifying performance and reliability of various systems whose execution are defined with likelihood. However, its inability to scale limits its applicability in practice. This thesis presents a new model checker, STAMINA, with efficient and scalable model truncation for probabilistic verification. STAMINA uses a novel model reduction technique generating a finite state representations of large systems that are amenable to existing probabilistic model checking techniques. The proposed method is evaluated on several benchmark examples. Comparisons with another state-of-art tool demonstrates both accuracy and efficiency of the presented method.

We study the decidability and complexity of verification problems for infinite-state systems. A fundamental question in formal verification is if the behaviour of one process is reproducible by another. This inclusion problem can be studied for various models of computation and behavioural preorders. It is generally intractable or even undecidable already for very limited computational models. The aim of this work is to clarify the status of the decidability and complexity of some well-known inclusion problems for suitably restricted computational models. In particular, we address the problems of checking strong and weak simulation and trace inclusion for processes definable by one-counter automata (OCA), that consist of a finite control and a single counter ranging over the non-negative integers. We take special interest of the subclass of one-counter nets (OCNs), that cannot fully test the counter for zero and which is subsumed both by pushdown automata and Petri nets / vector addition systems. Our new results include the PSPACE-completeness of strong and weak simulation, and the undecidability of trace inclusion for OCNs. Moreover, we consider semantic preorders between OCA/OCN and finite systems and close some gaps regarding their complexity. Finally, we study deterministic processes, for which simulation and trace inclusion coincide.

<p>The complex behavior of computer systems offers many challenges for <i>formal verification</i>. The analysis quickly becomes difficult as the number of participating processes increases.</p><p>A <i>parameterized system</i> is a family of systems parameterized on a number <i>n</i>, typically representing the number of participating processes. The <i>uniform verification problem</i> — to check whether a property holds for each instance — is an infinite-state problem. The automated analysis of parameterized and infinite-state systems has been the subject of research over the last 15–20 years. Much of the work has focused on safety properties. Progress in verification of liveness properties has been slow, as it is more difficult in general.</p><p>In this thesis, we consider verification of parameterized and infinite-state systems, with an emphasis on liveness, in the verification framework called <i>regular model checking (RMC)</i>. In RMC, states are represented as words, sets of states as regular expressions, and the transition relation as a regular relation.</p><p>We extend the automata-theoretic approach to RMC. We define a <i>specification logic</i> sufficiently strong to specify systems representable using RMC, and linear temporal logic properties of such systems, and provide an automatic translation from a specification into an analyzable model.</p><p>We develop <i>acceleration techniques</i> for RMC which allow more uniform and automatic verification than before, with greater power. Using these techniques, we succeed to verify safety and liveness properties of parameterized protocols from the literature.</p><p>We present a novel <i>reachability based</i> verification method for verification of liveness, in a general setting. We implement the method for RMC, with promising results.</p><p>Finally, we develop a framework for the verification of dynamic networks based on graph transformation, which generalizes the systems representable in RMC. In this framework we verify the latest version of the DYMO routing protocol, currently being considered for standardization by the IETF.</p>

Stochastic models, in particular Continuous Time Markov Chains, are a commonly employed mathematical abstraction for describing natural or engineered dynamical systems. While the theory behind them is well-studied, their specification can be problematic in a number of ways. Firstly, the size and complexity of the model can make its description difficult without using a high-level language. Secondly, knowledge of the system is usually incomplete, leaving one or more parameters with unknown values, thus impeding further analysis. Sophisticated machine learning algorithms have been proposed for the statistically rigorous estimation and handling of this uncertainty; however, their applicability is often limited to systems with finite state-space, and there has not been any consideration for their use on high-level descriptions. Similarly, high-level formal languages have been long used for describing and reasoning about stochastic systems, but require a full specification; efforts to estimate parameters for such formal models have been limited to simple inference algorithms. This thesis explores how these two approaches can be brought together, drawing ideas from the probabilistic programming paradigm. We introduce ProPPA, a process algebra for the specification of stochastic systems with uncertain parameters. The language is equipped with a semantics, allowing a formal interpretation of models written in it. This is the first time that uncertainty has been incorporated into the syntax and semantics of a formal language, and we describe a new mathematical object capable of capturing this information. We provide a series of algorithms for inference which can be automatically applied to ProPPA models without the need to write extra code. As part of these, we develop a novel inference scheme for infinite-state systems, based on random truncations of the state-space. The expressive power and inference capabilities of the framework are demonstrated in a series of small examples as well as a larger-scale case study. We also present a review of the state-of-the-art in both machine learning and formal modelling with respect to stochastic systems. We close with a discussion of potential extensions of this work, and thoughts about different ways in which the fields of statistical machine learning and formal modelling can be further integrated.

Many important software systems, including communication protocols and concurrent and distributed algorithms generate infinite state-spaces. Model-checking which is the most prominent algorithmic technique for the verification of concurrent systems is restricted to the analysis of finite-state models. Algorithmic analysis of infinite-state models is complicated--most interesting properties are undecidable for sufficiently expressive classes of infinite-state models. In this thesis, we focus on the development of algorithmic analysis techniques for two important classes of infinite-state models: FIFO Systems and Parameterized Systems. FIFO systems consisting of a set of finite-state machines that communicate via unbounded, perfect, FIFO channels arise naturally in the analysis of distributed protocols. We study the problem of computing the set of reachable states of a FIFO system composed of piecewise components. This problem is closely related to calculating the set of all possible channel contents, i.e. the limit language. We present new algorithms for calculating the limit language of a system with a single communication channel and important subclasses of multi-channel systems. We also discuss the complexity of these algorithms. Furthermore, we present a procedure that translates a piecewise FIFO system to an abridged structure, representing an expressive abstraction of the system. We show that we can analyze the infinite computations of the more concrete model by analyzing the computations of the finite, abridged model. Parameterized systems are a common model of computation for concurrent systems consisting of an arbitrary number of homogenous processes. We study the reachability problem in parameterized systems of infinite-state processes. We describe a framework that combines Abstract Interpretation with a backward-reachability algorithm. Our key idea is to create an abstract domain in which each element (a) represents the lower bound on the number of processes at a control location and (b) employs a numeric abstract domain to capture arithmetic relations among variables of the processes. We also provide an extrapolation operator for the domain to guarantee sound termination of the backward-reachability algorithm.

Many important software systems, including communication protocols and concurrent and distributed algorithms generate infinite state-spaces. Model-checking which is the most prominent algorithmic technique for the verification of concurrent systems is restricted to the analysis of finite-state models. Algorithmic analysis of infinite-state models is complicated--most interesting properties are undecidable for sufficiently expressive classes of infinite-state models. In this thesis, we focus on the development of algorithmic analysis techniques for two important classes of infinite-state models: FIFO Systems and Parameterized Systems. FIFO systems consisting of a set of finite-state machines that communicate via unbounded, perfect, FIFO channels arise naturally in the analysis of distributed protocols. We study the problem of computing the set of reachable states of a FIFO system composed of piecewise components. This problem is closely related to calculating the set of all possible channel contents, i.e. the limit language. We present new algorithms for calculating the limit language of a system with a single communication channel and important subclasses of multi-channel systems. We also discuss the complexity of these algorithms. Furthermore, we present a procedure that translates a piecewise FIFO system to an abridged structure, representing an expressive abstraction of the system. We show that we can analyze the infinite computations of the more concrete model by analyzing the computations of the finite, abridged model. Parameterized systems are a common model of computation for concurrent systems consisting of an arbitrary number of homogenous processes. We study the reachability problem in parameterized systems of infinite-state processes. We describe a framework that combines Abstract Interpretation with a backward-reachability algorithm. Our key idea is to create an abstract domain in which each element (a) represents the lower bound on the number of processes at a control location and (b) employs a numeric abstract domain to capture arithmetic relations among variables of the processes. We also provide an extrapolation operator for the domain to guarantee sound termination of the backward-reachability algorithm.

The complex behavior of computer systems offers many challenges for formal verification. The analysis quickly becomes difficult as the number of participating processes increases. A parameterized system is a family of systems parameterized on a number n, typically representing the number of participating processes. The uniform verification problem — to check whether a property holds for each instance — is an infinite-state problem. The automated analysis of parameterized and infinite-state systems has been the subject of research over the last 15–20 years. Much of the work has focused on safety properties. Progress in verification of liveness properties has been slow, as it is more difficult in general. In this thesis, we consider verification of parameterized and infinite-state systems, with an emphasis on liveness, in the verification framework called regular model checking (RMC). In RMC, states are represented as words, sets of states as regular expressions, and the transition relation as a regular relation. We extend the automata-theoretic approach to RMC. We define a specification logic sufficiently strong to specify systems representable using RMC, and linear temporal logic properties of such systems, and provide an automatic translation from a specification into an analyzable model. We develop acceleration techniques for RMC which allow more uniform and automatic verification than before, with greater power. Using these techniques, we succeed to verify safety and liveness properties of parameterized protocols from the literature. We present a novel reachability based verification method for verification of liveness, in a general setting. We implement the method for RMC, with promising results. Finally, we develop a framework for the verification of dynamic networks based on graph transformation, which generalizes the systems representable in RMC. In this framework we verify the latest version of the DYMO routing protocol, currently being considered for standardization by the IETF.

In this dissertation, we study the verification of concurrent programs written in the programming language Erlang using infinite-state model-checking. Erlang is a widely used, higher order, dynamically typed, call-by-value functional language with algebraic data types and pattern-matching. It is further augmented with support for actor concurrency, i.e. asynchronous message passing and dynamic process creation. With decidable model-checking in mind, we identify actor communicating systems (ACS) as a suitable target model for an abstract interpretation of Erlang. ACS model a dynamic network of finite-state processes that communicate over a fixed, finite number of unordered, unbounded channels. Thanks to being equivalent to Petri nets, ACS enjoy good algorithmic properties. We develop a verification procedure that extracts a sound abstract model, in the form of an ACS, from a given Erlang program; the resulting ACS simulates the operational semantics of the input. Using this abstract model, we can conservatively verify coverability properties of the input program, i.e. a weak form of safety properties, with a Petri net model-checker. We have implemented this procedure in our tool Soter, which is the first sound verification tool for Erlang programs using infinite-state model-checking. In our experiments, we find that Soter is accurate enough to verify a range of interesting and non-trivial benchmarks. Even though ACS coverability is Expspace-complete, Soter's analysis of these verification problems is surprisingly quick. In order to improve the precision of our verification procedure with respect to recursion, we investigate an extension of ACS that allows pushdown processes: asynchronously communicating pushdown systems (ACPS). ACPS that satisfy the empty-stack constraint (a pushdown process may receive only when its stack is empty) are a popular subclass of ACPS with good decision and complexity properties. In the context of Erlang, the empty stack constraint is unfortunately not realistic. We introduce a relaxation of the empty-stack constraint for ACPS called the shaped stack constraint. Stacks that fit the shape constraint may reach arbitrary heights. Further, a process may execute any communication action (be it process creation, message send or retrieval) whether or not its stack is empty. We prove that coverability for shaped ACPS, i.e. ACPS that satisfy the shaped constraint, reduces to the decidable coverability problem for well-structured transition systems (WSTS). Thus, shaped ACPS enable the modelling and verification of a larger class of message passing programs. We establish a close connection between shaped ACPS and a novel extension of Petri nets: nets with nested coloured tokens (NNCT). Tokens in NNCT are of two types: simple and complex. Complex tokens carry an arbitrary number of coloured tokens. The rules of a NNCT can synchronise complex and simple tokens, inject coloured tokens into a complex token, and eject all tokens of a specified set of active colours to predefined places. We show that the coverability problem for NNCT is Tower-complete, a new complexity class for non-elementary decision problems introduced by Schmitz. To prove Tower-membership, we devise a geometrically inspired version of the Rackoff technique, and we obtain Tower-hardness by adapting Stockmeyer's ruler construction to NNCT. To our knowledge, NNCT is the first extension of Petri nets (belonging to the class of nets with an infinite set of token types) that is proven to have primitive recursive coverability. This result implies Tower-completeness of coverability for ACPS that satisfy the shaped stack constraint.

A major current challenge consists in extending formal methods in order to handle infinite-state systems. Infiniteness stems from the fact that the system operates on unbounded data structure such as stacks, queues, clocks, integers; as well as parameterization. Systems with unbounded data structure are natural models for reasoning about communication protocols, concurrent programs, real-time systems, etc. While parameterized systems are more suitable if the system consists of an arbitrary number of identical processes which is the case for cache coherence protocols, distributed algorithms and so forth. In this thesis, we consider model checking problems for certain fundamental classes of probabilistic infinite-state systems, as well as the verification of safety properties in parameterized systems. First, we consider probabilistic systems with unbounded data structures. In particular, we study probabilistic extensions of Lossy Channel Systems (PLCS), Vector addition Systems with States (PVASS) and Noisy Turing Machine (PNTM). We show how we can describe the semantics of such models by infinite-state Markov chains; and then define certain abstract properties, which allow model checking several qualitative and quantitative problems. Then, we consider parameterized systems and provide a method which allows checking safety for several classes that differ in the topologies (linear or tree) and the semantics (atomic or non-atomic). The method is based on deriving an over-approximation which allows the use of a symbolic backward reachability scheme. For each class, the over-approximation we define guarantees monotonicity of the induced approximate transition system with respect to an appropriate order. This property is convenient in the sense that it preserves upward closedness when computing sets of predecessors.