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

The Scenario-Aware Dataflow (SADF) model is based on concurrent actors that interact via channels. It combines streaming data and control to capture scenarios while incorporating hard and soft real-time aspects. To model data-flow computations that are subject to uncertainty, SADF models are equipped with random primitives. We propose to use probabilistic model checking to analyze uncertain SADF models. We show how measures such as expected time, long-run objectives like throughput, as well as timed reachability—can a given system configuration be reached within a deadline with high probability?—can be automatically determined. The crux of our method is a compositional semantics of SADF with exponential agent execution times combined with automated abstraction techniques akin to partial-order reduction. We present the semantics in detail and show how it accommodates the incorporation of execution platforms, enabling the analysis of energy consumption. The feasibility of our approach is illustrated by analyzing several quantitative measures of an MPEG-4 decoder and an industrial face recognition application.

Probabilistic Model Checking for Uncertain Scenario-Aware Data Flow

We present a new probabilistic model checker Storm. Using state-of-the-art libraries, we aim for both high performance and versatility. This extended abstract gives a brief overview of the features of Storm.

The Probabilistic Model Checker Storm (Extended Abstract).

We present a semantics of a probabilistic while-language with soft conditioning and continuous distributions which handles programs diverging with positive probability. To this end, we extend the probabilistic guarded command language (pGCL) with draws from continuous distributions and a score operator. The main contribution is an extension of the standard weakest preexpectation semantics to support these constructs. As a sanity check of our semantics, we define an alternative trace-based semantics of the language, and show that the two semantics are equivalent. Various examples illustrate the applicability of the semantics.

Weakest Preexpectation Semantics for Bayesian Inference

We present a graph-based tool for analysing Java programs operating on dynamic data structures It involves the generation of an abstract state space employing a user-defined graph grammar LTL model checking is then applied to this state space, supporting both structural and functional correctness properties The analysis is fully automated, procedure-modular, and provides informative visual feedback including counterexamples in the case of property violations

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Let this Graph Be Your Witness

Mobile telecommunication systems and fixed telecommunication networks are developed as stand-alone systems and exist as separate and independent systems, interconnected at just a few points. A main objective of third generation mobile systems is to specify mobile-specific functionality as an integral part of fixed networks. The paper addresses the (possible) integration of future mobile and fixed systems, UMTS and B-ISDN. It proposes the use of advanced broadband basic call functions for the support of mobile call setup and handover, addresses the common use of a communication infrastructure, and finally, investigates the support of handover by B-ISDN multi-party call capabilities.

Joost-Pieter Katoen

Papers

Probabilistic Model Checking for Uncertain Scenario-Aware Data Flow

The Probabilistic Model Checker Storm (Extended Abstract).

Weakest Preexpectation Semantics for Bayesian Inference

Let this Graph Be Your Witness

Functional integration of UMTS and B-ISDN