Algorithms and data structures Books

Book SynopsisIn modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance". Table of Contents1. Introduction. - 1.1 Motivation. -1.2 Distributed Programming Abstractions. 1.3 The End-to-End Argument. 1.4 Software Components. - 1.5 Classes of Algorithms. -1.6 Chapter Notes. 2. Basic Abstractions. - 2.1 Distributed Computation. - 2.2 Abstracting Processes. - 2.3 Cryptographic Abstractions. - 2.4 Abstracting Communication. - 2.5 Timing Assumptions. - 2.6 Abstracting Time. - 2.7 Distributed-System Models. - 2.8 Exercises. - 2.9 Solutions. - 2.10 Chapter Notes . - . - 3. Reliable Broadcast. - 3.1 Motivation. - 3.2 Best-Effort Broadcast. - 3.3 Regular Reliable Broadcast. - 3.4 Uniform Reliable Broadcast. - 3.5 Stubborn Broadcast. - 3.6 Logged Best-Effort Broadcast. - 3.7 Logged Uniform Reliable Broadcast. - 3.8 Probabilistic Broadcast. - 3.9 FIFO and Causal Broadcast. - 3.10 Byzantine Consistent Broadcast. - 3.11 Byzantine Reliable Broadcast. - 3.12 Byzantine Broadcast Channels. - 3.13 Exercises. - 3.14 Solutions. - 3.15 Chapter Notes . - . - 4. Shared Memory. - 4.1 Introduction. - 4.2 (1, N) Regular Register. - 4.3 (1, N) Atomic Register. - 4.4 (N, N) Atomic Register. - 4.5 (1, N) Logged Regular Register. - 4.6 (1,N) Byzantine Safe Register. - 4.7 (1, N) Byzantine Regular Register. - 4.8 (1,N) Byzantine Atomic Register. - 4.9 Exercises. - 4.10 Solutions. - 4.11 Chapter Notes . - . - 5. Consensus. - 5.1 Regular Consensus. - 5.2 Uniform Consensus. - 5.3 Uniform Consensus in the Fail-Noisy Model. - 5.4 Logged Consensus. - 5.5 Randomized Consensus. - 5.6 Byzantine Consensus. - 5.7 Byzantine Randomized Consensus. - 5.8 Exercises. - 5.9 Solutions. - 5.10 Chapter Notes . - . - 6. Consensus Variants. - 6.1 Total-Order Broadcast. - 6.2 Byzantine Total-Order Broadcast. - 6.3 Terminating Reliable Broadcast. - 6.4 Fast Consensus. - 6.5 Fast Byzantine Consensus. - 6.6 Non-blocking Atomic Commit. - 6.7 Group Membership. - 6.8 View-Synchronous Communication. - 6.9 Exercises. - 6.10 Solutions. - 6.11 Chapter Notes . - . - 7. Concluding Remarks. - 7.1 Implementation in Appia. - 7.2 Further Implementations. - 7.3 Further Reading

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Book SynopsisThis book constitutes the proceedings of the International Conference on Information Security and Assurance, held in Brno, Czech Republic in August 2011.

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Book SynopsisComputer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the 21st century, which will be dominated by biology and biochemistry, similar to the role of mathematics in the physical sciences of the 20th century. In this award-winning best-seller, the author and his co-author focus on the fundamentals of computer science, which revolve around the notion of the algorithm. They discuss the design of algorithms, and their efficiency and correctness, the inherent limitations of algorithms and computation, quantum algorithms, concurrency, large systems and artificial intelligence. Throughout, the authors, in their own words, stress the ‘fundamental and robust nature of the science in a form that is virtually independent of the details of specific computers, languages and formalisms'. This version of the book is published to celebrate 25 years since its first edition, and in honor of the Alan M. Turing Centennial year. Turing was a true pioneer of computer science, whose work forms the underlying basis of much of this book. Trade ReviewFrom the reviews of the third edition:“This book should be on any short list for a central course in computer science. It is designed to provide a uniform background on which all students might draw. It has a good-humored, easy style, which would make any reader unwilling to close the book after opening it anywhere. All computer scientists should have this book. … the bibliography is organized in a convenient chapter-by-chapter form, which makes the book useful for advanced work, and the exercises will help instructors identify capable students.” (Harvey Cohn, ACM Computing Reviews, August, 2012)“This is a reprint of the 3rd edition on the occasion of the 25th year of the existence of the book; it is also intended to honor Alan Turing’s 100th birthday. … it is highly readable, even if one is largely acquainted with the field. It is very well written, containing many illustrative examples, suited also for the non-specialist.” (Gunther Schmidt, Zentralblatt MATH, Vol. 1243, 2012)Table of ContentsPreliminaries.- and Historical Review.- Algorithms and Data.- Programming Languages and Paradigms.- Methods and Analysis.- Algorithmic Methods.- The Correctness of Algorithms.- The Efficiency of Algorithms.- Limitations and Robustness.- Inefficiency and Intractability.- Noncomputability and Undecidability.- Algorithmic Universality and Its Robustness.- Relaxing the Rules.- Parallelism, Concurrency, and Alternative Models.- Probabilistic Algorithms.- Cryptography and Reliable Interaction.- The Bigger Picture.- Software Engineering.- Reactive Systems.- Algorithmics and Intelligence.

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Book SynopsisTo learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field.The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know.The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.Trade Review"This book builds a well-defined computation model that allows concepts that are important in technical and scientific applications -- like pointers, arrays and recursion -- to be gradually and rigorously introduced. The languages covered by the book, C and MATLAB, are highly relevant to engineering applications.Clarity of exposition, numerous well-chosen examples, pedagogical savvy, and logical sequencing of the topics all help the reader's progress through the chapters and make for an enjoyable learning experience. This book prepares one well to deal with advanced programming language constructs and the design of large, complex applications by promoting mastery of the fundamentals, by covering important practical aspects of a programmer's activity, and by instilling good design and implementation habits. It is therefore ideally suited for self-study or as a textbook in an introductory college-level programming course for engineers and similarly technically-minded students."Fabio Somenzi (University of Colorado at Boulder)Table of ContentsChap. 1, Memory: The Stack.- Chap. 2, Control.- Chap. 3, Arrays and Strings.- Chap. 4, Debugging.- Chap. 5, I/O.- Chap. 6, Memory: The Heap.- Chap. 7, Abstract Data Types.- Chap. 8, Linked Lists.- Chap. 9, Introduction to Matlab.- Chap. 10, Exploring ODEs with Matlab.- Chap. 11, Exploring Time and Frequency Domains with Matlab.- Chap. 12, Index.

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Book SynopsisDas Buch Arithmetik ist eine Übersetzung des vierten Kapitels der legendären Werkreihe "The Art of Computer Programming" von Donald E. Knuth in der neuesten Fassung. Es handelt sich um eine umfangreiche Einführung in die Computeralgebra, die den neuesten Stand der Forschung berücksichtigt. Donald E. Knuth versteht es, die Algorithmen didaktisch sehr geschickt und ohne Kompromisse bei der Strenge aufzubereiten. Das Buch enthält außerdem Hunderte von Aufgaben verschiedener Schwierigkeitsgrade mit Lösungen. Der Übersetzer, Prof. Dr. R. Loos, lehrt an der Universität Tübingen.Table of Contents4 — Arithmetik.- 4.1. Stellenwertsysteme.- 4.2. Gleitkomma-Aritlunetik.- 4.2.1. Einfachgenaue Rechnungen.- 4.2.2. Genauigkeit der Gleitkonuna-Arithmetik.- *4.2.3. Doppeltgenaue Rechnungen.- 4.2.4. Verteilung von Gleitkomrnazahlen.- 4.3. Mehrfachgenaue Aritlunetik.- 4.3.1. Die klassischen Algorithmen.- *4.3.2. Modulare Aritlnnetik.- *4.3.3. Wie schnell könn en wir multiplizieren?.- 4.4. Basiswechsel.- 4.5. Rationale Arithmetik.- 4.5.1. Brüche.- 4.5.2. Der größte gemeinsame Teiler.- *4.5.3. Analyse des euklidschen Algorithmus.- 4.5.4. Zerlegung in Prirnfaktoren.- 4.6. Polynornarithmetik.- 4.6.1. Division von Polynomen.- *4.6.2. Faktorisierung von Polynomen.- 4.6.3. Auswertung von Potenzen.- 4.6.4. Auswertung von Polynomen.- *4.7. Operationen an Potenzreihen.- Lösungen zu den Übungsaufgaben.- Anhang A — Tafeln numerischer Größen.- 1. Fundamentale Konstanten (dezimal).- 2. Fundamentale Konstanten (oktal).- 3. Harrnonische Zahlen , Bernoulli-Zahlen, Fibonacci-Zahlen.- Anhang B — Index der Bezeichnungen.- Index und Glossar.

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Book SynopsisThe development of powerful computer algebra systems has considerably ex­ tended the scope of problems of scientific computing which can now be solved successfully with the aid of computers. However, as the field of applications of computer algebra in scientific computing becomes broader and more complex, there is a danger of separation between theory, systems, and applications. For this reason, we felt the need to bring together the researchers who now ap­ ply the tools of computer algebra for the solution of problems in scientific computing, in order to foster new and closer interactions. CASC'99 is the second conference devoted to applications of computer al­ gebra in scientific computing. The first conference in this sequence, CASC'98, was held 20-24 April 1998 in St. Petersburg, Russia. This volume contains revised versions of the papers submitted by the par­ ticipants and accepted by the program committee after a thorough reviewing process. The collection of papers included in the proceedings covers various topics of computer algebra methods, algorithms and software applied to scien­ tific computing: symbolic-numeric analysis and solving differential equations, efficient computations with polynomials, groups, matrices and other related objects, special purpose programming environments, application to physics, mechanics, optics and to other areas. In particular, a significant group of papers deals with applications of com­ puter algebra methods for the solution of current problems in group theory, which mostly arise in mathematical physics.Table of ContentsSolution of Ordinary Differential Equations with MathLie.- Analysis of Stability of Rational Approximations through Computer Algebra.- An Automatic Symbolic-Numeric Taylor Series ODE Solver.- About Normal Form Method.- Computer Algebra Investigation of Equivalence in 4-node Plane Stress/Strain Finite Elements.- Symmetry Theorems for the Newtonian 4- and 5-body Problems with Equal Masses.- Symbolic Derivation of Different Class of High-order Compact Schemes for Partial Differential Equations.- Implementation of Aerodynamic Computations with Mathematica.- Completion of Linear Differential Systems to Involution.- Constrained Hamiltonian Systems and Gröbner Bases.- Construction of Involutive Monomial Sets for Different Involutive Divisions.- Partial Inverse Heuristic for the Approximate Solution of Non-linear Equations.- Computing Cocycles on Simplicial Complexes.- Bifurcations of Maps in the Software Package CONTENT.- Extending a Java Based Framework for Scientific Software-Components.- Symbolic-numeric Investigations for Stability Analysis of Satellite Systems.- Quantization by Presentation: The Nambu-Goto String in 1+3 Dimensions.- One Algorithm of Finding Solutions for the Systems with First Integrals.- Cohomology of Lie Superalgebras of Hamiltonian Vector Fields: Computer Analysis.- Computer Algebra Tools in Construction of Renormgroup Symmetries 251.- Where Numerics Can Benefit from Computer Algebra in Finite Difference Modelling of Fluid Flows.- Effectively Computation of Some Radicals of Submodules of Free Modules.- Computations on Character Tables of Association Schemes.- Investigation of Subgroup Embeddings by the Computer Algebra Package GAP.- An Investigation into Stability of Conservative Mechanical Systems Using Analytic Calculations.- Superfast Computations with Singular Structured Matrices over Abstract Fields.- From Modeling to Simulation with Symbolic Computation: An Application to Design and Performance Analysis of Complex Optical Devices.- A Symbolic Numeric Environment for Analyzing Measurement Data in Multi-Model Settings (Extended Abstract).- Geometric Interpretation of Strong Inconsistency in Knowledge Based Systems.- Indices and Solvability for General Systems of Differential Equations.- Decomposing Systems of Polynomial Equations.- Polynomials with Coefficients of Limited Accuracy.- Localization of Roots of a Polynomial not Represented in Canonical Form.- On Normalization of a Class of Polynomial Hamiltonians: From Ordinary and Inverse Points of View.- On Multivariate Polynomial Decomposition.- Complexity of Monomial Evaluations and Duality.- On the Simplification of Nonlinear DAE Systems in Analog Circuit Design.- Symbolic Analysis of Computational Algorithms with SYDNA.

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Book SynopsisThis self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix.The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition.Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.Trade Review“Every line of the book reflects that the author is the leading expert for hierarchical matrices. … Hierarchical matrices: algorithms and analysis is without a doubt a beautiful, comprehensive introduction to hierarchical matrices that can serve as both a graduate level textbook and a valuable resource for future research.” (Thomas Mach, Mathematical Reviews, April, 2017)“The book ‘Hierarchical matrices: algorithms and analysis’ is a self-contained monograph which presents an efficient possibility to handle the numerical treatment of fully populated large scale matrices appearing in scientific computations, and therefore it is of interest to scientists in computational mathematics, physics, chemistry and engineering.” (Constantin Popa, zbMATH 1336.65041, 2016)Table of ContentsPreface.- Part I: Introductory and Preparatory Topics.- 1. Introduction.- 2. Rank-r Matrices.- 3. Introductory Example.- 4. Separable Expansions and Low-Rank Matrices.- 5. Matrix Partition.- Part II: H-Matrices and Their Arithmetic.- 6. Definition and Properties of Hierarchical Matrices.- 7. Formatted Matrix Operations for Hierarchical Matrices.- 8. H2-Matrices.- 9. Miscellaneous Supplements.- Part III: Applications.- 10. Applications to Discretised Integral Operators.- 11. Applications to Finite Element Matrices.- 12. Inversion with Partial Evaluation.- 13. Eigenvalue Problems.- 14. Matrix Functions.- 15. Matrix Equations.- 16. Tensor Spaces.- Part IV: Appendices.- A. Graphs and Trees.- B. Polynomials.- C. Linear Algebra and Functional Analysis.- D. Sinc Functions and Exponential Sums.- E. Asymptotically Smooth Functions.- References.- Index.

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