Texts in Theoretical Computer Science. An EATCS Series – serie

Software programs are formal entities with precise meanings independent of their programmers, so the transition from ideas to programs necessarily involves a formalisation at some point.The first part of this graduate-level introduction to formal methods develops an understanding of what constitutes formal methods and what their place is in Software Engineering. It also introduces logics as languages to describe reasoning and the process algebra CSP as a language to represent behaviours. The second part offers specification and testing methods for formal development of software, based on the modelling languages CASL and UML. The third part takes the reader into the application domains of normative documents, human machine interfaces, and security.  Use of notations and formalisms is uniform throughout the book.Topics and features:Explains foundations, and introduces specification, verification, and testing methodsExploresvarious application domainsPresents realistic and practical examples, illustrating conceptsBrings together contributions from highly experienced educators and researchers Offers modelling and analysis methods for formal development of softwareSuitable for graduate and undergraduate courses in software engineering, this uniquely practical textbook will also be of value to students in informatics, as well as to scientists and practical engineers,  who want to learn about or work more effectively with formal theories and methods.Markus Roggenbach is a Professor in the Dept. of Computer Science of Swansea University. Antonio Cerone is an Associate Professor in the Dept. of Computer Science of Nazarbayev University, Nur-Sultan. Bernd-Holger Schlingloff is a Professor in the Institut für Informatik of Humboldt-Universität zu Berlin. Gerardo Schneider is a Professor in the Dept. of Computer Science and Engineering of University of Gothenburg. Siraj Ahmed Shaikh is a Professor in the Institute for Future Transport and Cities of Coventry University.The companion site for the book offers additional resources, including further material for selected chapters, prepared lab classes, a list of errata, slides and teaching material, and virtual machines with preinstalled tools and resources for hands-on experience with examples from the book. The URL is: https://sefm-book.github.io

Software programs are formal entities with precise meanings independent of their programmers, so the transition from ideas to programs necessarily involves a formalisation at some point.The first part of this graduate-level introduction to formal methods develops an understanding of what constitutes formal methods and what their place is in Software Engineering. It also introduces logics as languages to describe reasoning and the process algebra CSP as a language to represent behaviours. The second part offers specification and testing methods for formal development of software, based on the modelling languages CASL and UML. The third part takes the reader into the application domains of normative documents, human machine interfaces, and security.  Use of notations and formalisms is uniform throughout the book.Topics and features:Explains foundations, and introduces specification, verification, and testing methodsExploresvarious application domainsPresents realistic and practical examples, illustrating conceptsBrings together contributions from highly experienced educators and researchers Offers modelling and analysis methods for formal development of softwareSuitable for graduate and undergraduate courses in software engineering, this uniquely practical textbook will also be of value to students in informatics, as well as to scientists and practical engineers,  who want to learn about or work more effectively with formal theories and methods.Markus Roggenbach is a Professor in the Dept. of Computer Science of Swansea University. Antonio Cerone is an Associate Professor in the Dept. of Computer Science of Nazarbayev University, Nur-Sultan. Bernd-Holger Schlingloff is a Professor in the Institut für Informatik of Humboldt-Universität zu Berlin. Gerardo Schneider is a Professor in the Dept. of Computer Science and Engineering of University of Gothenburg. Siraj Ahmed Shaikh is a Professor in the Institute for Future Transport and Cities of Coventry University.The companion site for the book offers additional resources, including further material for selected chapters, prepared lab classes, a list of errata, slides and teaching material, and virtual machines with preinstalled tools and resources for hands-on experience with examples from the book. The URL is: https://sefm-book.github.io

This book presents the fundamentals of concurrency theory with clarity and rigor. The authors start with the semantic structure, namely labelled transition systems, which provides us with the means and the tools to express processes, to compose them, and to prove properties they enjoy. The rest of the book relies on Milner's Calculus of Communicating Systems, tailored versions of which are used to study various notions of equality between systems, and to investigate in detail the expressive power of the models considered.The authors proceed from very basic results to increasingly complex issues, with many examples and exercises that help to reveal the many subtleties of the topic. The book is suitable for advanced undergraduate and graduate students in computer science and engineering, and scientists engaged with theories of concurrency.

This book presents the fundamentals of concurrency theory with clarity and rigor. The authors start with the semantic structure, namely labelled transition systems, which provides us with the means and the tools to express processes, to compose them, and to prove properties they enjoy. The rest of the book relies on Milner's Calculus of Communicating Systems, tailored versions of which are used to study various notions of equality between systems, and to investigate in detail the expressive power of the models considered.The authors proceed from very basic results to increasingly complex issues, with many examples and exercises that help to reveal the many subtleties of the topic. The book is suitable for advanced undergraduate and graduate students in computer science and engineering, and scientists engaged with theories of concurrency.

This textbook explains online computation in different settings, with particular emphasis on randomization and advice complexity. These settings are analyzed for various online problems such as the paging problem, the k-server problem, job shop scheduling, the knapsack problem, the bit guessing problem, and problems on graphs.This book is appropriate for undergraduate and graduate students of computer science, assuming a basic knowledge in algorithmics and discrete mathematics. Also researchers will find this a valuable reference for the recent field of advice complexity.

This book presents in their basic form the most important models of computation, their basic programming paradigms, and their mathematical descriptions, both concrete and abstract. Each model is accompanied by relevant formal techniques for reasoning on it and for proving some properties. After preliminary chapters that introduce the notions of structure and meaning, semantic methods, inference rules, and logic programming, the authors arrange their chapters into parts on IMP, a simple imperative language; HOFL, a higher-order functional language; concurrent, nondeterministic and interactive models; and probabilistic/stochastic models.The authors have class-tested the book content over many years, and it will be valuable for graduate and advanced undergraduate students of theoretical computer science and distributed systems, and for researchers in this domain. Each chapter of the book concludes with a list of exercises addressing the key techniques introduced, solutions to selected exercises are offered at the end of the book.

Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics.

This textbook explains online computation in different settings, with particular emphasis on randomization and advice complexity. These settings are analyzed for various online problems such as the paging problem, the k-server problem, job shop scheduling, the knapsack problem, the bit guessing problem, and problems on graphs.This book is appropriate for undergraduate and graduate students of computer science, assuming a basic knowledge in algorithmics and discrete mathematics. Also researchers will find this a valuable reference for the recent field of advice complexity.

This book presents in their basic form the most important models of computation, their basic programming paradigms, and their mathematical descriptions, both concrete and abstract.

Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics.

Reactive systems are becoming more and more important for essentially all areas of technical and professional activities as well as for many areas of everyday life. The design of these systems is a great challenge and requires sound compromises between safety and time-to-market. To meet these needs, early design phases nowadays include verification of given specifications against system descriptions to find potential design errors as early as possible. This book is devoted to the foundation of the most popular formal methods for the specification and verification of reactive systems. In particular, the ��-calculus, omega-automata, and temporal logics are covered in full detail; their relationship and state-of-the-art verification procedures based on these formal approaches are presented. Furthermore, the advantages and disadvantages of the formalisms from particular points of view are analyzed. Most results are given with detailed proofs, so that the presentation is almost self-contained. This book is targeted to advanced students, lecturers and researchers in the area of formal methods.

This book gives a broad overview of core topics of finite model theory: expressive power, descriptive complexity, and zero-one laws, together with selected applications to database theory and artificial intelligence, especially constraint databases and constraint satisfaction problems. The final chapter provides a concise modern introduction to modal logic, which emphasizes the continuity in spirit and technique with finite model theory. This underlying spirit involves the use of various fragments of, and hierarchies within, first order, second order, fixed point, and infinitary logics to gain insight into phenomena in complexity theory and combinatorics. Students of logic and computer science will find here the tools necessary to embark on research in finite model theory, and all readers will experience the excitement of a vibrant area of application of logic to computer science.

With the rapid developments in hardware technologies, distributed computing and the interconnected world became realities, and the term "communication" became central in computer science. Solving communication tasks under different circumstances is the topic of this textbook. It provides an introduction to the theory of design and the analysis of algorithms for the dissemination of information in interconnection networks, with a special emphasis on broadcast and gossip. The book starts with the classic telegraph and telephone communication modes and follows the technology up to optical switches. Despite the rigorous presentation, simplicity and transparency are the main learning features of this book. All ideas, concepts, algorithms, analyses and arguments are first explained in an informal way in order to develop the right intuition, and then they are carefully specified in detail. This makes the content accessible for beginners as well as specialists.

The aim of this textbook is not only to provide an elegant route through the theoretical fundamentals of computer science, but also to show that theoretical computer science is a fascinating discipline, full of spectacular contributions and miracles, and depth in research, and yet directly applicable. Thus, we aim to excite people about its study. To achieve these goals we do not hesitate to take a lot of space to present motivations, and especially to give the informal development of crucial ideas and concepts and their transparent, but rigorous presentation.An additional aim is to present the development of the computer scientist's way of thinking, so we do not restrict this book to the classic areas like computability and automata theory but we also present fundamental concepts such as approximation and randomization in algorithmics and we explain the basic ideas of cryptography and interconnection network design.

The parametric lambda calculus is a metamodel for reasoning about various kinds of computations. Its syntactic definition is based on the notion of "sets of input values", and different lambda calculi can be obtained from it by instantiating such sets in suitable ways. The parametric lambda calculus is used as a tool for presenting in a uniform way basic notions of programming languages, and for studying with a uniform approach some lambda calculi modeling different kinds of computations, such as call-by-name, both in its lazy and non-lazy versions, and call-by-value. The parametric presentation allows us both to prove in one step all the fundamental properties of different calculi, and to compare them with each other. The book includes some classical results in the field of lambda calculi, but completely rephrased using the parametric approach, together with some new results. The lambda calculi are presented from a computer science viewpoint, with particular emphasis on their semantics, both operational and denotational.This book is dedicated to researchers, and can be used as a textbook for masters or Ph.D. courses on the foundations of computer science.

Coq is an interactive proof assistant for the development of mathematical theories and formally certified software. It is based on a theory called the calculus of inductive constructions, a variant of type theory.This book provides a pragmatic introduction to the development of proofs and certified programs using Coq. With its large collection of examples and exercises it is an invaluable tool for researchers, students, and engineers interested in formal methods and the development of zero-fault software.

The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation.The emphasis is on fully normalizing machines based on a full-fledged beta-reduction as an essential prerequisite for symbolic computations that treat functions and variables truly as first-class objects. Their weakly normalizing counterparts are shown to be functional abstract machines that sacrifice the flavors of full beta-reductions for decidedly simpler runtime structures and improved runtime efficiency. Further downgrading of the lambda calculus leads to classical imperative (von Neumann) machines that permit side-effecting operations on the runtime environment.

The art, craft, discipline, logic, practice and science of developing large-scale software products needs a professional base. The textbooks in this three-volume set combine informal, engineeringly sound approaches with the rigor of formal, mathematics-based approaches. This volume covers the basic principles and techniques of abstraction and modeling. First it provides a sound, simple basis of insight into discrete mathematics: numbers, sets, Cartesians, types, functions, the Lambda calculus, algebras and mathematical logic. Then it teaches its readers basic property- and model-oriented specification principles and techniques. The model-oriented concepts that are common to such specification languages as B, VDM-SL and Z are propagated here through the use of the RAISE specification language (RSL). Finally the book covers the basic principles of functional, imperative and parallel specification programming.This book is targeted at university undergraduate students and at college lecturers.

The art, craft, discipline, logic, practice and science of developing large-scale software products needs a professional base. The textbooks in this three-volume set combine informal, engineeringly sound approaches with the rigor of formal, mathematics-based approaches. This volume covers the basic principles and techniques of specifying systems and languages. It deals with modeling the semiotics (pragmatics, semantics and syntax of systems and languages), modeling spatial and simple temporal phenomena, and such specialized topics as modularity (incl. UML class diagrams), Petri nets, live sequence charts, statecharts, and temporal logics, including the duration calculus. Finally, the book presents techniques for interpreter and compiler development of functional, imperative, modular and parallel programming languages.This book is targeted at late undergraduate to early graduate university students, and researchers of programming methodologies. Vol. 1 of this series is a prerequisite text.

The art, craft, discipline, logic, practice and science of developing large-scale software products needs a professional base. The textbooks in this three-volume set combine informal, engineeringly sound approaches with the rigor of formal, mathematics-based approaches. Advocating a novel approach based on understanding the application domain before formulating the requirements, the book takes the reader from the principles and techniques for the development of domain descriptions, via principles and techniques for the derivation of requirements prescriptions from domain models, to principles and techniques for the refinement of requirements into software designs: architectures and component design. Focusing only on the informal parts, this book targets undergraduate students in courses on software engineering and college lecturers in that field, while the full version of the book also targets advanced students, lecturers and researchers.

Finite model theory is an area of mathematical logic that grew out of computer science applications. The main sources of motivational examples for finite model theory are found in database theory, computational complexity, and formal languages, although in recent years connections with other areas, such as formal methods and verification, and artificial intelligence, have been discovered. The birth of finite model theory is often identified with Trakhtenbrot's result from 1950 stating that validity over finite models is not recursively enumerable; in other words, completeness fails over finite models. The tech­ nique of the proof, based on encoding Turing machine computations as finite structures, was reused by Fagin almost a quarter century later to prove his cel­ ebrated result that put the equality sign between the class NP and existential second-order logic, thereby providing a machine-independent characterization of an important complexity class. In 1982, Immerman and Vardi showed that over ordered structures, a fixed point extension of first-order logic captures the complexity class PTIME of polynomial time computable propertiE~s. Shortly thereafter, logical characterizations of other important complexity classes were obtained. This line of work is often referred to as descriptive complexity. A different line of finite model theory research is associated with the de­ velopment of relational databases. By the late 1970s, the relational database model had replaced others, and all the basic query languages for it were es­ sentially first-order predicate calculus or its minor extensions.

This book introduces the reader to the grammatical theory of picture generation, focussing on issues that are of particular interest for computer scientists. Using picture generation as a vehicle, many of the general ideas of the theory of computation are exemplified by results about (un)decidable, NP-complete, or efficiently solvable problems, normal forms, hierarchies of language classes, and related phenomena.Many of the devices and results discussed in the book extend those known from the literature, or are original ones, including a novel approach to generating colored pictures.The software on the enclosed CD-ROM lets you try out all examples or even extend the system.

This book presents sequential decision theory from a novel algorithmic information theory perspective. While the former is suited for active agents in known environments, the latter is suited for passive prediction in unknown environments. The book introduces these two different ideas and removes the limitations by unifying them to one parameter-free theory of an optimal reinforcement learning agent embedded in an unknown environment. Most AI problems can easily be formulated within this theory, reducing the conceptual problems to pure computational ones. Considered problem classes include sequence prediction, strategic games, function minimization, reinforcement and supervised learning. The discussion includes formal definitions of intelligence order relations, the horizon problem and relations to other approaches. One intention of this book is to excite a broader AI audience about abstract algorithmic information theory concepts, and conversely to inform theorists about exciting applications to AI.

Modern cryptology increasingly employs mathematically rigorous concepts and methods from complexity theory. Conversely, current research topics in complexity theory are often motivated by questions and problems from cryptology. This book takes account of this situation, and therefore its subject is what may be dubbed "cryptocomplexity'', a kind of symbiosis of these two areas.This book is written for undergraduate and graduate students of computer science, mathematics, and engineering, and can be used for courses on complexity theory and cryptology, preferably by stressing their interrelation. Moreover, it may serve as a valuable source for researchers, teachers, and practitioners working in these fields. Starting from scratch, it works its way to the frontiers of current research in these fields and provides a detailed overview of their history and their current research topics and challenges.

A man may imagine he understands something, but still not understand anything in the way that he ought to. (Paul of Tarsus, 1 Corinthians 8:2) Calling this a ‘practical theory’ may require some explanation. Theory and practice are often thought of as two di?erent worlds, governed bydi?erentideals,principles, andlaws.DavidLorgeParnas, forinstance,who hascontributedmuchtoourtheoreticalunderstandingofsoftwareengineering and also to sound use of theory in the practice of it, likes to point out that ‘theoretically’ is synonymous to ‘not really’. In applied mathematics the goal is to discover useful connections between these two worlds. My thesis is that in software engineering this two-world view is inadequate, and a more intimate interplay is required between theory and practice. That is, both theoretical and practical components should be integrated into a practical theory. It should beclearfrom theabovethattheintended readership of this book is not theoreticians. They would probably have di?culties in appreciating a book on theory where the presentation does not proceed in a logical sequence from basic de?nitions to theorems and mathematical proofs, followed by - plication examples. In fact, all this would not constitute what I understand by a practical theory in this context.

Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities.Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms ? foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. ? while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.

Parameterized complexity theory is a recent branch of computational complexity theory that provides a framework for a refined analysis of hard algorithmic problems. The central notion of the theory, fixed-parameter tractability, has led to the development of various new algorithmic techniques and a whole new theory of intractability.This book is a state-of-the-art introduction to both algorithmic techniques for fixed-parameter tractability and the structural theory of parameterized complexity classes, and it presents detailed proofs of recent advanced results that have not appeared in book form before. Several chapters are each devoted to intractability, algorithmic techniques for designing fixed-parameter tractable algorithms, and bounded fixed-parameter tractability and subexponential time complexity. The treatment is comprehensive, and the reader is supported with exercises, notes, a detailed index, and some background on complexity theory and logic.The book will be of interest to computer scientists, mathematicians and graduate students engaged with algorithms and problem complexity.

J. Casti, Five More Golden Rules, Wiley, New York, 2000, p. 262.

There are several approaches to attack hard problems. All have their merits, but also their limitations, and need a large body of theory as their basis. A number of books for each one exist: books on complexity theory, others on approximation algorithms, heuristic approaches, parametrized complexity, and yet others on randomized algorithms. This book discusses thoroughly all of the above approaches. And, amazingly, at the same time, does this in a style that makes the book accessible not only to theoreticians, but also to the non-specialist, to the student or teacher, and to the programmer. Do you think that mathematical rigor and accessibility contradict? Look at this book to find out that they do not, due to the admirable talent of the author to present his material in a clear and concise way, with the idea behind the approach spelled out explicitly, often with a revealing example.Reading this book is a beautiful experience and I can highly recommend it to anyone interested in learning how to solve hard problems. It is not just a condensed union of material from other books.Because it discusses the different approaches in depth, it has the chance to compare them in detail, and, most importantly, to highlight under what circumstances which approach might be worth exploring. No book on a single type of solution can do that, but this book does it in an absolutely fascinating way that can serve as a pattern for theory textbooks with a high level of generality. (Peter Widmayer)The second edition extends the part on the method of relaxation to linear programming with an emphasis on rounding, LP-duality, and primal-dual schema, and provides a self-contained and transparent presentation of the design of randomized algorithms for primality testing.