ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

From the Publisher:
Among the many approaches to formal reasoning about programs, Dynamic Logic enjoys the singular advantage of being strongly related to classical logic. Its variants constitute natural generalizations and extensions of classical formalisms. For example, Propositional Dynamic Logic (PDL) can be described as a blend of three complementary classical ingredients: propositional calculus, modal logic, and the algebra of regular events. In First-Order Dynamic Logic (DL), the propositional calculus is replaced by classical first-order predicate calculus. Dynamic Logic is a system of remarkable unity that is theoretically rich as well as of practical value. It can be used for formalizing correctness specifications and proving rigorously that those specifications are met by a particular program. Other uses include determining the equivalence of programs, comparing the expressive power of various programming constructs, and synthesizing programs from specifications. 
This book provides the first comprehensive introduction to Dynamic Logic. It is divided into three parts. The first part reviews the appropriate fundamental concepts of logic and computability theory and can stand alone as an introduction to these topics. The second part discusses PDL and its variants, and the third part discusses DL and its variants. Examples are provided throughout, and exercises and a short historical section are included at the end of each chapter.

Dynamic Logic

bases were introduced in [Smy77] where they are called “R-structures”. Examples of abstract bases are concrete bases of continuous domains, of course, where the relation≺ is the restriction of the order of approximation. Axiom (INT) is satisfied because of Lemma 2.2.15 and because we have required bases in domains to have directed sets of approximants for each element. Other examples are partially ordered sets, where (INT) is satisfied because of reflexivity. We will shortly identify posets as being exactly the bases of compact elements of algebraic domains. In what follows we will use the terminology developed at the beginning of this chapter, even though the relation ≺ on an abstract basis need neither be reflexive nor antisymmetric. This is convenient but in some instances looks more innocent than it is. An idealA in a basis, for example, has the property (following from directedness) that for everyx ∈ A there is another element y ∈ A with x ≺ y. In posets this doesn’t mean anything but here it becomes an important feature. Sometimes this is stressed by using the expression ‘ A is a round ideal’. Note that a set of the form↓x is always an ideal because of (INT) but that it need not contain x itself. We will refrain from calling ↓x ‘principal’ in these circumstances. Definition 2.2.21. For a basis〈B,≺〉 let Idl(B) be the set of all ideals ordered by inclusion. It is called theideal completionof B. Furthermore, leti : B → Idl(B) denote the function which maps x ∈ B to ↓x. If we want to stress the relation with whichB is equipped then we write Idl(B,≺) for the ideal completion. Proposition 2.2.22.Let 〈B,≺〉 be an abstract basis.

Domain theory

Extensively class tested, this text takes an innovative approach to explaining the process of software testing: it defines testing as the process of applying a few well-defined, general-purpose test criteria to a structure or model of the software. The structure of the text directly reflects the pedagogical approach and incorporates the latest innovations in testing, including techniques to test modern types of software such as OO, web applications, and embedded software.

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Introduction to Software Testing

Introduction to Software Testing: List of Figures

From the Publisher:
Provides a simple and clear presentation, covering propositional and predicate logic and some specialized logics used for reasoning about the correctness of computer systems.

/pdf/logic-in-computer-science-modelling-and-reasoning-about-1xmdohrju1.pdf

Logic in Computer Science: Modelling and Reasoning about Systems

We present Kripke modal transition systems (Kripke MTSs), a generalization of modal transition systems [27, 26], as a foundation for three-valued program analysis. The semantics of Kripke MTSs are presented by means of a mixed power domain of states; soundness and consistency are proved. Two major applications, model checking partial state spaces and three-valued program shape analysis, are presented as evidence of the suitability of Kripke MTSs as a foundation for three-valued analyses.

/pdf/modal-transition-systems-a-foundation-for-three-valued-8o983soscc.pdf

Modal Transition Systems: A Foundation for Three-Valued Program Analysis

We present a framework for automatic program abstraction that can be used for model checking any formula of the modal mu-calculus. Unlike traditional conservative abstractions which can only prove universal properties, our framework can both prove and disprove any formula including arbitrarily nested path quantifiers. We discuss algorithms for automatically generating an abstract Modal Transition System (MTS) by adapting existing predicate and cartesian abstraction techniques. We showthat model checking arbitrary formulas using abstract MTSs can be done at the same computational cost as model checking universal formulas using conservative abstractions.

Abstraction-Based Model Checking Using Modal Transition Systems

Many notions of models in computer science provide quantitative information, or uncertainties, which necessitate a quantitative model checking paradigm. We present such a framework for reactive and generative systems based on a non-standard interpretation of the modal mu-calculus, where /spl mu/x./spl phi//vx./spl phi/ are interpreted as least/greatest fired points over the infinite lattice of maps from states to the unit interval. By letting formulas denote lower bounds of probabilistic evidence of properties, the values computed by our quantitative model checker can serve as satisfactory correctness guarantees in cases where conventional qualitative model checking fails. Since fixed point iteration in this infinite domain is computationally unfeasible, we establish that the computation of fixed points may be restated as a conventional, and on average efficient, optimization problem in linear programming; this holds for a fragment of the modal mu-calculus which subsumes CTL. Our semantics induces a state equivalence which is strictly in between probabilistic bisimulation and probabilistic ready bisimulation.

Michael Huth

Papers

Logic in Computer Science: Modelling and Reasoning about Systems

Modal Transition Systems: A Foundation for Three-Valued Program Analysis

Abstraction-Based Model Checking Using Modal Transition Systems

Quantitative analysis and model checking

Future developments in cyber risk assessment for the internet of things