You are previewing Algorithms in C, Parts 1-4: Fundamentals, Data Structures, Sorting, Searching, Third Edition.
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Algorithms in C, Parts 1-4: Fundamentals, Data Structures, Sorting, Searching, Third Edition

Book Description

Robert Sedgewick has thoroughly rewritten and substantially expanded his popular work to provide current and comprehensive coverage of important algorithms and data structures. Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 250,000 programmers!

This particular book, Parts 1-4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. The algorithms and data structures are expressed in concise implementations in C, so that you can both appreciate their fundamental properties and test them on real applications. Of course, the substance of the book applies to programming in any language.

Highlights

  • Expanded coverage of arrays, linked lists, strings, trees, and other basic data structures

  • Greater emphasis on abstract data types (ADTs) than in previous editions

  • Over 100 algorithms for sorting, selection, priority queue ADT implementations, and symbol table ADT (searching) implementations

  • New implementations of binomial queues, multiway radix sorting, Batcher's sorting networks, randomized BSTs, splay trees, skip lists, multiway tries, and much more

  • Increased quantitative information about the algorithms, including extensive empirical studies and basic analytic studies, giving you a basis for comparing them

  • Over 1000 new exercises to help you learn the properties of algorithms

  • Whether you are a student learning the algorithms for the first time or a professional interested in having up-to-date reference material, you will find a wealth of useful information in this book.

    Table of Contents

    1. About This eBook
    2. Title Page
    3. Copyright Page
    4. Preface
      1. Scope
      2. Use in the Curriculum
      3. Algorithms of Practical Use
      4. Programming Language
      5. Acknowledgments
    5. Dedication Page
    6. Notes on Exercises
    7. Contents
    8. Part One: Fundamentals
      1. Chapter One. Introduction
        1. 1.1 Algorithms
        2. 1.2 A Sample Problem: Connectivity
        3. Exercises
        4. 1.3 Union–Find Algorithms
        5. Exercises
        6. 1.4 Perspective
        7. Exercises
        8. 1.5 Summary of Topics
      2. Chapter Two. Principles of Algorithm Analysis
        1. 2.1 Implementation and Empirical Analysis
        2. Exercises
        3. 2.2 Analysis of Algorithms
        4. Exercises
        5. 2.3 Growth of Functions
        6. Exercises
        7. 2.4 Big-Oh Notation
        8. Exercises
        9. 2.5 Basic Recurrences
        10. Exercises
        11. 2.6 Examples of Algorithm Analysis
        12. Exercises
        13. 2.7 Guarantees, Predictions, and Limitations
        14. Exercise
      3. References for Part One
    9. Part Two: Data Structures
      1. Chapter Three. Elementary Data Structures
        1. 3.1 Building Blocks
        2. Exercises
        3. 3.2 Arrays
        4. Exercises
        5. 3.3 Linked Lists
        6. Exercises
        7. 3.4 Elementary List Processing
        8. Exercises
        9. 3.5 Memory Allocation for Lists
        10. Exercises
        11. 3.6 Strings
        12. Exercises
        13. 3.7 Compound Data Structures
        14. Exercises
      2. Chapter Four. Abstract Data Types
        1. 4.1 Abstract Objects and Collections of Objects
        2. Exercises
        3. 4.2 Pushdown Stack ADT
        4. Exercises
        5. 4.3 Examples of Stack ADT Clients
        6. Exercises
        7. 4.4 Stack ADT Implementations
        8. Exercises
        9. 4.5 Creation of a New ADT
        10. Exercises
        11. 4.6 FIFO Queues and Generalized Queues
        12. Exercises
        13. 4.7 Duplicate and Index Items
        14. Exercises
        15. 4.8 First-Class ADTs
        16. Exercises
        17. 4.9 Application-Based ADT Example
        18. Exercises
        19. 4.10 Perspective
      3. Chapter Five. Recursion and Trees
        1. 5.1 Recursive Algorithms
        2. Exercises
        3. 5.2 Divide and Conquer
        4. Exercises
        5. 5.3 Dynamic Programming
        6. Exercises
        7. 5.4 Trees
        8. Exercises
        9. 5.5 Mathematical Properties of Binary Trees
        10. Exercises
        11. 5.6 Tree Traversal
        12. Exercises
        13. 5.7 Recursive Binary-Tree Algorithms
        14. Exercises
        15. 5.8 Graph Traversal
        16. Exercises
        17. 5.9 Perspective
      4. References for Part Two
    10. Part Three: Sorting
      1. Chapter Six. Elementary Sorting Methods
        1. 6.1 Rules of the Game
        2. Exercises
        3. 6.2 Selection Sort
        4. Exercises
        5. 6.3 Insertion Sort
        6. Exercises
        7. 6.4 Bubble Sort
        8. Exercises
        9. 6.5 Performance Characteristics of Elementary Sorts
        10. Exercises
        11. 6.6 Shellsort
        12. Exercises
        13. 6.7 Sorting of Other Types of Data
        14. Exercises
        15. 6.8 Index and Pointer Sorting
        16. Exercises
        17. 6.9 Sorting of Linked Lists
        18. Exercises
        19. 6.10 Key-Indexed Counting
        20. Exercises
      2. Chapter Seven. Quicksort
        1. 7.1 The Basic Algorithm
        2. Exercises
        3. 7.2 Performance Characteristics of Quicksort
        4. Exercises
        5. 7.3 Stack Size
        6. Exercises
        7. 7.4 Small Subfiles
        8. Exercises
        9. 7.5 Median-of-Three Partitioning
        10. Exercises
        11. 7.6 Duplicate Keys
        12. Exercises
        13. 7.7 Strings and Vectors
        14. Exercises
        15. 7.8 Selection
        16. Exercises
      3. Chapter Eight. Merging and Mergesort
        1. 8.1 Two-Way Merging
        2. Exercises
        3. 8.2 Abstract In-place Merge
        4. Exercises
        5. 8.3 Top-Down Mergesort
        6. Exercises
        7. 8.4 Improvements to the Basic Algorithm
        8. Exercises
        9. 8.5 Bottom-Up Mergesort
        10. Exercises
        11. 8.6 Performance Characteristics of Mergesort
        12. Exercises
        13. 8.7 Linked-List Implementations of Mergesort
        14. Exercises
        15. 8.8 Recursion Revisited
        16. Exercises
      4. Chapter Nine. Priority Queues and Heapsort
        1. Exercises
        2. 9.1 Elementary Implementations
        3. Exercises
        4. 9.2 Heap Data Structure
        5. Exercises
        6. 9.3 Algorithms on Heaps
        7. Exercises
        8. 9.4 Heapsort
        9. Exercises
        10. 9.5 Priority-Queue ADT
        11. Exercises
        12. 9.6 Priority Queues for Index Items
        13. Exercises
        14. 9.7 Binomial Queues
        15. Exercises
      5. Chapter Ten. Radix Sorting
        1. 10.1 Bits, Bytes, and Words
        2. Exercises
        3. 10.2 Binary Quicksort
        4. Exercises
        5. 10.3 MSD Radix Sort
        6. Exercises
        7. 10.4 Three-Way Radix Quicksort
        8. Exercises
        9. 10.5 LSD Radix Sort
        10. Exercises
        11. 10.6 Performance Characteristics of Radix Sorts
        12. Exercises
        13. 10.7 Sublinear-Time Sorts
        14. Exercises
      6. Chapter Eleven. Special-Purpose Sorting Methods
        1. 11.1 Batcher’s Odd–Even Mergesort
        2. Exercises
        3. 11.2 Sorting Networks
        4. Exercises
        5. 11.3 External Sorting
        6. Exercises
        7. 11.4 Sort–Merge Implementations
        8. Exercises
        9. 11.5 Parallel Sort–Merge
        10. Exercises
      7. References for Part Three
    11. Part Four: Searching
      1. Chapter Twelve. Symbol Tables and Binary Search Trees
        1. 12.1 Symbol-Table Abstract Data Type
        2. Exercises
        3. 12.2 Key-Indexed Search
        4. Exercises
        5. 12.3 Sequential Search
        6. Exercises
        7. 12.4 Binary Search
        8. Exercises
        9. 12.5 Binary Search Trees (BSTs)
        10. Exercises
        11. 12.6 Performance Characteristics of BSTs
        12. Exercises
        13. 12.7 Index Implementations with Symbol Tables
        14. Exercises
        15. 12.8 Insertion at the Root in BSTs
        16. Exercises
        17. 12.9 BST Implementations of Other ADT Functions
        18. Exercises
      2. Chapter Thirteen. Balanced Trees
        1. Exercises
        2. 13.1 Randomized BSTs
        3. Exercises
        4. 13.2 Splay BSTs
        5. Exercises
        6. 13.3 Top-Down 2-3-4 Trees
        7. Exercises
        8. 13.4 Red–Black Trees
        9. Exercises
        10. 13.5 Skip Lists
        11. Exercises
        12. 13.6 Performance Characteristics
        13. Exercises
      3. Chapter Fourteen. Hashing
        1. 14.1 Hash Functions
        2. Exercises
        3. 14.2 Separate Chaining
        4. Exercises
        5. 14.3 Linear Probing
        6. Exercises
        7. 14.4 Double Hashing
        8. Exercises
        9. 14.5 Dynamic Hash Tables
        10. Exercises
        11. 14.6 Perspective
        12. Exercises
      4. Chapter Fifteen. Radix Search
        1. 15.1 Digital Search Trees
        2. Exercises
        3. 15.2 Tries
        4. Exercises
        5. 15.3 Patricia Tries
        6. Exercises
        7. 15.4 Multiway Tries and TSTs
        8. Exercises
        9. 15.5 Text-String–Index Algorithms
        10. Exercises
      5. Chapter Sixteen. External Searching
        1. 16.1 Rules of the Game
        2. 16.2 Indexed Sequential Access
        3. Exercises
        4. 16.3 B Trees
        5. Exercises
        6. 16.4 Extendible Hashing
        7. Exercises
        8. 16.5 Perspective
        9. Exercises
    12. References for Part Four
    13. Index
    14. Code Snippets