Algorithmen - Eine Einführung

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Author: Thomas H. Cormen,Charles E. Leiserson,Ronald Rivest,Clifford Stein

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110522012

Category: Computers

Page: 1339

View: 365

Der "Cormen" bietet eine umfassende und vielseitige Einführung in das moderne Studium von Algorithmen. Es stellt viele Algorithmen Schritt für Schritt vor, behandelt sie detailliert und macht deren Entwurf und deren Analyse allen Leserschichten zugänglich. Sorgfältige Erklärungen zur notwendigen Mathematik helfen, die Analyse der Algorithmen zu verstehen. Den Autoren ist es dabei geglückt, Erklärungen elementar zu halten, ohne auf Tiefe oder mathematische Exaktheit zu verzichten. Jedes der weitgehend eigenständig gestalteten Kapitel stellt einen Algorithmus, eine Entwurfstechnik, ein Anwendungsgebiet oder ein verwandtes Thema vor. Algorithmen werden beschrieben und in Pseudocode entworfen, der für jeden lesbar sein sollte, der schon selbst ein wenig programmiert hat. Zahlreiche Abbildungen verdeutlichen, wie die Algorithmen arbeiten. Ebenfalls angesprochen werden Belange der Implementierung und andere technische Fragen, wobei, da Effizienz als Entwurfskriterium betont wird, die Ausführungen eine sorgfältige Analyse der Laufzeiten der Programme mit ein schließen. Über 1000 Übungen und Problemstellungen und ein umfangreiches Quellen- und Literaturverzeichnis komplettieren das Lehrbuch, dass durch das ganze Studium, aber auch noch danach als mathematisches Nachschlagewerk oder als technisches Handbuch nützlich ist. Für die dritte Auflage wurde das gesamte Buch aktualisiert. Die Änderungen sind vielfältig und umfassen insbesondere neue Kapitel, überarbeiteten Pseudocode, didaktische Verbesserungen und einen lebhafteren Schreibstil. So wurden etwa - neue Kapitel zu van-Emde-Boas-Bäume und mehrfädigen (engl.: multithreaded) Algorithmen aufgenommen, - das Kapitel zu Rekursionsgleichungen überarbeitet, sodass es nunmehr die Teile-und-Beherrsche-Methode besser abdeckt, - die Betrachtungen zu dynamischer Programmierung und Greedy-Algorithmen überarbeitet; Memoisation und der Begriff des Teilproblem-Graphen als eine Möglichkeit, die Laufzeit eines auf dynamischer Programmierung beruhender Algorithmus zu verstehen, werden eingeführt. - 100 neue Übungsaufgaben und 28 neue Problemstellungen ergänzt. Umfangreiches Dozentenmaterial (auf englisch) ist über die Website des US-Verlags verfügbar.

An Introduction to Data Structures and Algorithms

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Author: J.A. Storer

Publisher: Springer Science & Business Media

ISBN: 146120075X

Category: Computers

Page: 599

View: 1709

Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel

Data Structures and Algorithms: A First Course

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Author: Iain T. Adamson

Publisher: Springer Science & Business Media

ISBN: 1447110234

Category: Computers

Page: 419

View: 9869

All young computer scientists who aspire to write programs must learn something about algorithms and data structures. This book does exactly that. Based on lecture courses developed by the author over a number of years the book is written in an informal and friendly way specifically to appeal to students. The book is divided into four parts: the first on Data Structures introduces a variety of structures and the fundamental operations associated with them, together with descriptions of how they are implemented in Pascal; the second discusses algorithms and the notion of complexity; Part III is concerned with the description of successively more elaborate structures for the storage of records and algorithms for retrieving a record from such a structure by means of its key; and finally, Part IV consists of very full solutions to nearly all the exercises in the book.

Data Structures and Algorithms in Java

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Author: Adam Drozdek

Publisher: Cengage Learning

ISBN: 0534492525

Category: Computers

Page: 650

View: 1691

Using the Java programming language, author Adam Drozdek highlights three important aspects of data structures and algorithms. First, the book places special emphasis on the connection between data structures and their algorithms, including an analysis of the algorithms’ complexity. Second, the book presents data structures in the context of object-oriented program design, stressing the principle of information hiding in its treatment of encapsulation and decomposition. Finally, the book closely examines data structure implementation. Overall, this practical and theoretical book prepares students with a solid foundation in data structures for future courses and work in design implementation, testing, or maintenance of virtually any software system. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Data Structures and Algorithms in C++

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Author: Adam Drozdek

Publisher: Cengage Learning

ISBN: 0534491820

Category: Computers

Page: 650

View: 9276

Using the C++ programming language, author Adam Drozdek highlights three important aspects of data structures and algorithms. First, the book places special emphasis on the connection between data structures and their algorithms, including an analysis of the algorithms' complexity. Second, the book presents data structures in the context of object-oriented program design, stressing the principle of information hiding in its treatment of encapsulation and decomposition. Finally, the book closely examines data structure implementation. Overall, this practical and theoretical book prepares students with a solid foundation in data structures for future courses and work in design implementation, testing, or maintenance of virtually any software system. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Data Structures and Algorithms Using Java

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Author: William McAllister

Publisher: Jones & Bartlett Publishers

ISBN: 1449660967

Category: Computers

Page: 580

View: 4237

With an accessible writing style and manageable amount of content, Data Structures and Algorithms Using Java is the ideal text for your course. This outstanding text correlates to the recommended syllabus put forth by the Association of Computing Machinery standard curriculum guidelines. The author has produced a resource that is more readable and instructional than any other, without compromising the scope of the ACM CS103, Data Structures and Algorithms, course material. The text’s unique, student-friendly pedagogical approach and organizational structure will keep students engaged in the process of self-directed investigative discovery both inside and outside the classroom. The pedagogical features of the text, based on the author’s 30 years of teaching experience, include succinct code examples, a unique common template used as the organizational basis of each chapter, the use of pseudocode to present the major algorithms developed in the text, nearly 300 carefully designed figures, and a concise review of Java.

Data Structures and Algorithms Using C#

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Author: Michael McMillan

Publisher: Cambridge University Press

ISBN: 0521670152

Category: Computers

Page: 355

View: 4583

Michael McMillan discusses the implementation of data structures and algorithms from the .NET framework. The comprehensive text includes basic data structures and algorithms plus advanced algorithms such as probabilistic algorithms and dynamics programming.

Algorithmen in C

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Author: Robert Sedgewick

Publisher: Pearson Deutschland GmbH

ISBN: 9783893193769

Category: Algorithmus

Page: 742

View: 1522

Data Structures and Algorithms

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Author: Shi Kuo Chang

Publisher: World Scientific

ISBN: 9812383484

Category: Computers

Page: 347

View: 434

This is an excellent, up-to-date and easy-to-use text on data structures and algorithms that is intended for undergraduates in computer science and information science. The thirteen chapters, written by an international group of experienced teachers, cover the fundamental concepts of algorithms and most of the important data structures as well as the concept of interface design. The book contains many examples and diagrams. Whenever appropriate, program codes are included to facilitate learning.This book is supported by an international group of authors who are experts on data structures and algorithms, through its website at http: //www.cs.pitt.edu/ jung/GrowingBook/, so that both teachers and students can benefit from their expertise

Data Structures And Algorithms

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Author: N.A.Deshpande S.S.Sane

Publisher: Technical Publications

ISBN: 9788184310849

Category:

Page: 476

View: 6439

Fundamental ConceptsData Structures : Data, Data objects, Data types, Abstract Data Types (ADT) and Data structure, Concept of primitive and non primitive, Linear and non-linear, Static and dynamic, Persistent and ephemeral data structures,Introduction to algorithms : Definition and characteristics of an algorithm, Algorithm design.Tools : Flowcharts and pseudo code, Notations : Algorithm Header, Purpose, Conditions and return, Statements, Statement numbers, Variables, Comments, Statement constructs : Sequence, Selection, Loops and sub-algorithms.Program development : Analysis design, Coding, Testing and verification.Linear Data Structures using Sequential OrganizationConcept of sequential organization, Arrays as ADT, Storage representation of array (row major and column major). Representation of polynomials using arrays, Representation of sparse matrix, Addition, Transpose and fast transpose of sparse matrix, Time and space complexity analysis for simple and fast transpose for sparse matrix.Stacks Fundamentals, Stacks as ADT, Representation and implementation of stack using arrays, Applications of stack : Expression evaluation and conversion, Reversing a string, Parsing : Well-form parenthesis, Decimal to binary conversion, Representation of multiple stacks using single array.Recursion : Definition, Writing recursive functions, How recursion works ? Simulating recursion using stack.QueuesFundamentals, Queue as ADT, Representation and implementation of queue using arrays, Circular queue : Representation and implementation, Applications of queue : Josephus problem, Job scheduling, Queue simulation, Categorizing data, Doubly ended queue, Representation of multiple queues using single array, Priority queue.Searching and SortingSearching : Sequential, Binary and index sequential search.Sorting : General concepts : Sort order, Sort stability, Efficiency and passes, Bubble sort, Selection sort, Insertion sort, Shell, Radix, Quick and merge sort.Algorithm Analysis and StrategiesAlgorithm analysis : Time complexity : Real time and frequency count, Big 'O' and notations, Space complexity : Compile-time and run-time, Best, Average and worst cases. Algorithmic strategies : Use and the peculiar characteristics of each type, Divide and conquer (Quick sort/Tower of Hanoi), Backtracking (Eight queens problem), Greedy (Job scheduling with deadlines), Dynamic programming (Example triangulation problem) (Implementation not expected for all the examples).Programming Laboratory

Advanced Data Structures and Algorithms

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Author: A.A.Puntambekar

Publisher: Technical Publications

ISBN: 9788184314786

Category:

Page: 614

View: 8093

C++ class overview - Class definition, Objects, Class members, Access control, Class scope, Constructors and destructors, Parameter passing methods, Inline functions, Static class members, This pointer, Friend functions, Dynamic memory allocation and deallocation (new and delete), Exception handling. Function overloading, Operator overloading, Generic programming - Function and class templates, Inheritance basics, Base and derived classes, Inheritance types, Base class access control, Runtime polymorphism using virtual functions, Abstract classes, Streams I/O. Algorithms, Performance analysis-time complexity and space complexity, O-notation, Omega notation and Theta notation, Review of basic data structures - The list ADT, Stack ADT, Queue ADT, Implementation using template classes in C++, Sparse matrix representation. Dictionaries, Linear list representation, Skip list representation, Operations - Insertion, Deletion and searching, Hash table representation, Hash functions, Collision resolution-separate chaining, Open addressing-linear probing, Quadratic probing, Double hashing, Rehashing, Extendible hashing, Comparison of hashing and skip lists. Priority queues - Definition, ADT, Realizing a priority queue using heaps, Definition, Insertion, Deletion, Application-Heap sort, External sorting - Model for external sorting, Multiway merge, Polyphase merge. Search trees (Part I) : Binary search trees, Definition, ADT, Implementation, Operations-searching, Insertion and deletion, Balanced search trees - AVL trees, Definition, Height of an AVL tree, Representation, Operations-insertion, Deletion and searching. Search trees (Part II) : Red - Black trees and splay trees, B-Trees-B-Tree of order m, Height of a B-Tree, Insertion, Deletion and searching, Comparison of search trees.Divide and Conquer-General method, Applications - Binary search, Merge sort, Quick sort, Strassen s matrix multiplication. Efficient non recursive tree traversal algorithms, Biconnected components. Disjoint set operations, Union and find algorithms. Greedy method and Dynamic programming : General method (Greedy), Minimum cost spanning trees, Job sequencing with deadlines, General method (Dynamic programming), Optimal binary search trees, 0/1 Knapsack problem, Ordering matrix multiplications.

Data Structures And Algorithms

Made Easy.

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Author: Harry. H. Chaudhary.

Publisher: Programmers Mind LLC New York.

ISBN: N.A

Category: Computers

Page: 250

View: 7402

Features of Book - Essential Data Structures Skills -- Made Easy! All Code/Algo written in C Programming. || Learn with Fun strategy. Anyone can comfortably follow this book to Learn DSA Step By Step. Unique strategy- Concepts, Problems, Analysis, Questions, Solutions. Why This Book - This book gives a good start and complete introduction for data structures and algorithms for Beginner’s. While reading this book it is fun and easy to read it. This book is best suitable for first time DSA readers, Covers all fast track topics of DSA for all Computer Science students and Professionals. Learn all Concept’s Clearly with World Famous Programmer Harry Chaudhary. Main Objective - Data structures is concerned with the storage, representation and manipulation of data in a computer. In this book, we discuss some of the more versatile and popular data structures used to solve a variety of useful problems. Among the topics are linked lists, stacks, queues, trees, graphs, sorting and hashing. What Special - Data Structures & Algorithms Using C or C++ takes a gentle approach to the data structures course in C Providing an early, text gives students a firm grasp of key concepts and allows those experienced in another language to adjust easily. Flexible by design,. Finally, a solid foundation in building and using abstract data types is alsoprovided. Using C, this book develops the concepts & theory of data structures and algorithm analysis in a gradual, step-by-step manner, proceeding from concrete examples to abstract principles. Standish covers a wide range of both traditional and contemporary software engineering topics. This is a handy guide of sorts for any computer science Students, This book is a solution bank for various problems related to data structures and algorithms. It can be used as a reference manual by Computer Science Engineering students. This Book also covers all aspects of CS, IT. Special Note: Digital Pdf Edition || Epub Edition is Available on Google Play & Books. less

R Data Structures and Algorithms

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Author: Dr. PKS Prakash,Achyutuni Sri Krishna Rao

Publisher: Packt Publishing Ltd

ISBN: 1786464160

Category: Computers

Page: 276

View: 5184

Increase speed and performance of your applications with efficient data structures and algorithms About This Book See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and sorting algorithms Understand important concepts such as big-o notation, dynamic programming, and functional data structured Who This Book Is For This book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected. What You Will Learn Understand the rationality behind data structures and algorithms Understand computation evaluation of a program featuring asymptotic and empirical algorithm analysis Get to know the fundamentals of arrays and linked-based data structures Analyze types of sorting algorithms Search algorithms along with hashing Understand linear and tree-based indexing Be able to implement a graph including topological sort, shortest path problem, and Prim's algorithm Understand dynamic programming (Knapsack) and randomized algorithms In Detail In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. Style and approach This easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.

Swift Data Structure and Algorithms

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Author: Erik Azar,Mario Eguiluz Alebicto

Publisher: Packt Publishing Ltd

ISBN: 1785884654

Category: Computers

Page: 286

View: 1621

Master the most common algorithms and data structures, and learn how to implement them efficiently using the most up-to-date features of Swift 3 About This Book Develop a deep understanding of the collections in the Swift Standard Library with this step-by-step guide Develop native Swift data structures and algorithms for use in mobile, desktop, and server-based applications Learn about performance efficiency between different data structures and algorithms Who This Book Is For This book is for developers who want to learn how to implement and use common data structures and algorithms natively in Swift. Whether you are a self-taught developer without a formal technical background or you have a degree in Computer Science, this book will provide with the knowledge you need to develop advanced data structures and algorithms in Swift using the latest language features. What You Will Learn Get to know about the basic data structures and how to use the Swift REPL Use the Swift Standard Library collections bridging to Objective-C collections, and find out about protocol-oriented programming Find out about Swift generators and sequences, and see how to use them to implement advanced data structures such as Stack, StackList, Queue, and LinkedList Implement sorting algorithms such as Insertion Sort, Merge Sort, and Quick Sort and understand the performance trade-offs between them See how to implement various binary trees, B-Tree, and Splay Trees Perform advanced searching methods using Red-Black trees, AVL trees, and Trie trees, and take a look at several substring search algorithms Get to know about the data structures used in graphs and how to implement graphs such as depth-first search, breadth-first search, directed graphs, spanning tree, and shortest path Explore algorithm efficiency and see how to measure it In Detail Apple's Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple's legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That's what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You'll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You'll also see how to choose the perfect algorithm for your problem. Style and approach This easy-to-follow yet comprehensive guide can either be read from beginning to end, or depending on your current knowledge level, you can jump to the specific chapter that interests you. Each chapter topic starts with an introduction to the topic and algorithm before moving on to the hands-on implementation and analysis.

Algorithms and Data Structures for External Memory

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Author: Jeffrey Scott Vitter

Publisher: Now Publishers Inc

ISBN: 1601981066

Category: Computers

Page: 174

View: 8406

Algorithms and Data Structures for External Memory describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.