Our growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a given system satisfies a desired property such as deadlock freedom, invariants, and request-response properties. This automated technique for verification and debugging has developed into a mature and widely used approach with many applications. Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field. The book begins with the basic principles for modeling concurrent and communicating systems, introduces different classes of properties (including safety and liveness), presents the notion of fairness, and provides automata-based algorithms for these properties. It introduces the temporal logics LTL and CTL, compares them, and covers algorithms for verifying these logics, discussing real-time systems as well as systems subject to random phenomena. Separate chapters treat such efficiency-improving techniques as abstraction and symbolic manipulation. The book includes an extensive set of examples (most of which run through several chapters) and a complete set of basic results accompanied by detailed proofs. Each chapter concludes with a summary, bibliographic notes, and an extensive list of exercises of both practical and theoretical nature.

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Principles of Model Checking

N G van Kampen 1981 Amsterdam: North-Holland xiv + 419 pp price Dfl 180 This is a book which, at a lower price, could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes, as well as those who just enjoy a beautifully written book. It provides an extensive graduate-level introduction which is clear, cautious, interesting and readable.

https://iopscience.iop.org/article/10.1088/0031-9112/34/4/040/pdf

Stochastic Processes in Physics and Chemistry

This paper describes a major new release of the PRISMprobabilistic model checker, adding, in particular, quantitative verification of (priced) probabilistic timed automata. These model systems exhibiting probabilistic, nondeterministic and real-time characteristics. In many application domains, all three aspects are essential; this includes, for example, embedded controllers in automotive or avionic systems, wireless communication protocols such as Bluetooth or Zigbee, and randomised security protocols. PRISM, which is open-source, also contains several new components that are of independent use. These include: an extensible toolkit for building, verifying and refining abstractions of probabilistic models; an explicit-state probabilistic model checking library; a discrete-event simulation engine for statistical model checking; support for generation of optimal adversaries/strategies; and a benchmark suite.

http://www.prismmodelchecker.org/papers/cav11.pdf

PRISM 4.0: verification of probabilistic real-time systems

This paper presents the overal structure, the design criteria, and the main features of the tool box Uppaal. It gives a detailed user guide which describes how to use the various tools of Uppaal version 2.02 to construct abstract models of a real-time system, to simulate its dynamical behavior, to specify and verify its safety and bounded liveness properties in terms of its model. In addition, the paper also provides a short review on case-studies where Uppaal is applied, as well as references to its theoretical foundation.

UPPAAL in a Nutshell

Real and Complex Analysis

This paper proposes a Functional Architecture and a corresponding Network Architecture for the Universal Mobile Telecommunication System (UMTS). Procedures like call handling, location management, and handover are considered. The architecture covers the domestic, business, and public environments. Integration with existing and forthcoming networks for xed communications is anticipated and the Intelligent Network (IN) philosophy is applied.

A UMTS network architecture

Bayesian networks (BNs) are probabilistic graphical models for describing complex joint probability distributions. The main problem for BNs is inference: Determine the probability of an event given observed evidence. Since exact inference is often infeasible for large BNs, popular approximate inference methods rely on sampling.

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How long, O Bayesian network, will I sample thee?

One of the central objectives of the LOTOS restandardisation activity is to define an enhanced LOTOS language which supports real-time specification. The timed extension is based upon a timed LOTOS proposal called ET-LOTOS (Enhanced Timed LOTOS). This paper defines a (branching-time) non-interleaving semantics for ET-LOTOS without data. As a denotational model, a suitable timed extension of R. Langerak's (1992, 1993) bundle event structures is used. For guarded recursive processes, we show the consistency between our non-interleaving semantics and the ET-LOTOS interleaving semantics. Since our semantic model does not have an explicit notion of the passage of time (as opposed to the interleaving semantics), we are able to handle unguarded recursion and Zeno behaviours in a perspicuous way.

A true concurrency semantics for ET-LOTOS

This paper shows that the satisfiability problems for a bounded fragment of probabilistic CTL (called bounded PCTL) and an extension of the modal μ-calculus with probabilistic quantification over next-modalities (called PμTL) are decidable. For bounded PCTL we provide an NEXPTIME-algorithm for the satisfiability problem and show that the logic has a small model property where the model size is independent from the probability bounds in the formula. We show that the satisfiability problem of a simple sub-logic of bounded PCTL is PSPACE-complete. We prove that PμTL has a small model property and that a decision procedure using 2 player parity games can be employed for the satisfiability problem of PμTL. These results imply that PμTL and qualitative PCTL formulas with only thresholds >0 and =1---are incomparable. We also establish that---in contrast to PCTL---every satisfiable PμTL-formula has a rational model, a model with rational probabilities only.

On the Satisfiability of Some Simple Probabilistic Logics

The results of this dissertation are two-fold. On the one hand, inductive learning techniques are extended and two new inference algorithms for inferring nondeterministic, and universal, respectively, finite-state automata are presented. On the other hand, certain learning techniques are employed and enhanced to semi-automatically infer communicating automata (also called design models in the software development cycle). For both topics, theoretical results on the feasibility of the approaches, as well as an implementation are presented which, in both cases, support our theory. Concerning the first objective to derive a so-called active online learning algorithm for nondeterministic finite-state automata (NFA), we present, in analogy to Angluin’s famous learning algorithm L [Ang87a] for deterministic finite-state automata (DFA), a version for inferring a certain subclass of NFA. The automata from this class are called residual finitestate automata (RFSA). It was shown by Denis et al. [DLT02] that there is an exponential gap between the size of minimal DFA and their corresponding minimal RFSA. Even if there are also cases where the canonical (i.e., minimal) RFSA is exponentially larger than a corresponding minimal NFA, we show that the new learning algorithm—called NL— is a great improvement compared to L as the inferred canonical RFSA has always at most the size of the corresponding minimal DFA but is usually even considerably smaller and more easy to learn. Unlike a learning procedure developed by Denis et al.—called DeLeTe2 [DLT04]—our algorithm is capable of deriving canonical RFSA. Like L, the new algorithm will be applicable in many fields including pattern recognition, computational linguistics and biology, speech recognition, and verification. From our point of view, NL might especially play a mayor role in the area of formal verification where the size of the models that are processed is of enormous importance and nondeterminism not regarded an unpleasant property. The second objective of this thesis is to create a method for inferring distributed design models (CFMs) from a given set of requirements specified as scenarios (message sequence charts). The main idea is to extend the L algorithm to cope with valid and invalid sets of system runs and, after some iterations, come up with an intermediate design model (a DFA) which exhibits features that make it distributable into communicating components (or processes) interacting via FIFO channels. Theoretical results on which classes of CFMs are learnable in which time-complexity bounds are presented. We also developed a tool implementation called Smyle, realizing important theoretical results evolving from this part of the thesis. Based on this learning formalism we also derive a software-engineering lifecycle model called the Smyle Modeling Approach in which we embedded our learning approach. Additionally, we launched a project for a new learning library called libalf which includes most of the learning algorithms (and their extensions) mentioned in this thesis. We hope that, due to its continuously increasing functionality, libalf will find broad acceptance among researchers, and that it will be the starting point for an extensive project of different research groups which will employ libalf, or augment the library with new algorithms.

Joost-Pieter Katoen

Papers

A UMTS network architecture

How long, O Bayesian network, will I sample thee?

A true concurrency semantics for ET-LOTOS

On the Satisfiability of Some Simple Probabilistic Logics

Learning communicating and nondeterministic automata