Turing Lecture from the winners of the 2007 ACM A.M. Turing Award. In 1981, Edmund M. Clarke and E. Allen Emerson, working in the USA, and Joseph Sifakis working independently in France, authored seminal papers that founded what has become the highly successful field of model checking. This verification technology provides an algorithmic means of determining whether an abstract model---representing, for example, a hardware or software design---satisfies a formal specification expressed as a temporal logic (TL) formula. Moreover, if the property does not hold, the method identifies a counterexample execution that shows the source of the problem. The progression of model checking to the point where it can be successfully used for complex systems has required the development of sophisticated means of coping with what is known as the state explosion problem. Great strides have been made on this problem over the past 28 years by what is now a very large international research community. As a result many major hardware and software companies are beginning to use model checking in practice. Examples of its use include the verification of VLSI circuits, communication protocols, software device drivers, real-time embedded systems, and security algorithms. The work of Clarke, Emerson, and Sifakis continues to be central to the success of this research area. Their work over the years has led to the creation of new logics for specification, new verification algorithms, and surprising theoretical results. Model checking tools, created by both academic and industrial teams, have resulted in an entirely novel approach to verification and test case generation. This approach, for example, often enables engineers in the electronics industry to design complex systems with considerable assurance regarding the correctness of their initial designs. Model checking promises to have an even greater impact on the hardware and software industries in the future. ---Moshe Y. Vardi, Editor-in-Chief

Model checking

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

Model Checking

SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level descriptions of distributed algorithms to detailed code for controlling telephone exchanges. The paper gives an overview of the design and structure of the verifier, reviews its theoretical foundation, and gives an overview of significant practical applications.

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The model checker SPIN

Symbolic model checking is a powerful formal specification and verification method that has been applied successfully in several industrial designs. Using symbolic model checking techniques it is possible to verify industrial-size finite state systems. State spaces with up to 1030 states can be exhaustively searched in minutes. Models with more than 10120 states have been verified using special techniques.

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Symbolic Model Checking

We describe a method for using abstraction to reduce the complexity of temporal-logic model checking. Using techniques similar to those involved in abstract interpretation, we construct an abstract model of a program without ever examining the corresponding unabstracted model. We show how this abstract model can be used to verify properties of the original program. We have implemented a system based on these techniques, and we demonstrate their practicality using a number of examples, including a program representing a pipelined ALU circuit with over 101300 states.

Model checking and abstraction

The state explosion problem remains a major hurdle in applying symbolic model checking to large hardware designs. State space abstraction, having been essential for verifying designs of industrial complexity, is typically a manual process, requiring considerable creativity and insight.In this article, we present an automatic iterative abstraction-refinement methodology that extends symbolic model checking. In our method, the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques that analyze such counterexamples and refine the abstract model correspondingly. We describe aSMV, a prototype implementation of our methodology in NuSMV. Practical experiments including a large Fujitsu IP core design with about 500 latches and 10000 lines of SMV code confirm the effectiveness of our approach.

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Counterexample-guided abstraction refinement for symbolic model checking

We describe a framework for compositional verification of finite-state processes. The framework is based on two ideas: a subset of the logic CTL for which satisfaction is preserved under composition, and a preorder on structures which captures the relation between a component and a system containing the component. Satisfaction of a formula in the logic corresponds to being below a particular structure (a tableau for the formula) in the preorder. We show how to do assume-guarantee-style reasoning within this framework. Additionally, we demonstrate efficient methods for model checking in the logic and for checking the preorder in several special cases. We have implemented a system based on these methods, and we use it to give a compositional verification of a CPU controller.

Orna Grumberg

Papers

Model checking

Model checking and abstraction

Counterexample-guided abstraction refinement for symbolic model checking

Model checking and modular verification

Characterizing finite Kripke structures in propositional temporal logic