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Data Structures and Algorithm Analysis in Java (3rd Edition).pdf

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    Cover
    Title Page
    Copyright Page
    Contents
    Preface
    Acknowledgments
    Chapter 1 Introduction
    1.1 What’s the Book About?
    1.2 Mathematics Review
    1.2.1 Exponents
    1.2.2 Logarithms
    1.2.3 Series
    1.2.4 Modular Arithmetic
    1.2.5 The P Word
    1.3 A Brief Introduction to Recursion
    1.4 Implementing Generic Components Pre-Java 5
    1.4.1 Using Object for Genericity
    1.4.2 Wrappers for Primitive Types
    1.4.3 Using Interface Types for Genericity
    1.4.4 Compatibility of Array Types
    1.5 Implementing Generic Components Using Java 5 Generics
    1.5.1 Simple Generic Classes and Interfaces
    1.5.2 Autoboxing/Unboxing
    1.5.3 The Diamond Operator
    1.5.4 Wildcards with Bounds
    1.5.5 Generic Static Methods
    1.5.6 Type Bounds
    1.5.7 Type Erasure
    1.5.8 Restrictions on Generics
    1.6 Function Objects
    Summary
    Exercises
    References
    Chapter 2 Algorithm Analysis
    2.1 Mathematical Background
    2.2 Model
    2.3 What to Analyze
    2.4 Running Time Calculations
    2.4.1 A Simple Example
    2.4.2 General Rules
    2.4.3 Solutions for the Maximum Subsequence Sum Problem
    2.4.4 Logarithms in the Running Time
    2.4.5 A Grain of Salt
    Summary
    Exercises
    References
    Chapter 3 Lists, Stacks, and Queues
    3.1 Abstract Data Types (ADTs)
    3.2 The List ADT
    3.2.1 Simple Array Implementation of Lists
    3.2.2 Simple Linked Lists
    3.3 Lists in the Java Collections API
    3.3.1 Collection Interface
    3.3.2 Iterators
    3.3.3 The List Interface, ArrayList, and LinkedList
    3.3.4 Example: Using remove on a LinkedList
    3.3.5 ListIterators
    3.4 Implementation of ArrayList
    3.4.1 The Basic Class
    3.4.2 The Iterator and Java Nested and Inner Classes
    3.5 Implementation of LinkedList
    3.6 The Stack ADT
    3.6.1 Stack Model
    3.6.2 Implementation of Stacks
    3.6.3 Applications
    3.7 The Queue ADT
    3.7.1 Queue Model
    3.7.2 Array Implementation of Queues
    3.7.3 Applications of Queues
    Summary
    Exercises
    Chapter 4 Trees
    4.1 Preliminaries
    4.1.1 Implementation of Trees
    4.1.2 Tree Traversals with an Application
    4.2 Binary Trees
    4.2.1 Implementation
    4.2.2 An Example: Expression Trees
    4.3 The Search Tree ADT—Binary Search Trees
    4.3.1 contains
    4.3.2 findMin and findMax
    4.3.3 insert
    4.3.4 remove
    4.3.5 Average-Case Analysis
    4.4 AVL Trees
    4.4.1 Single Rotation
    4.4.2 Double Rotation
    4.5 Splay Trees
    4.5.1 A Simple Idea (That Does Not Work)
    4.5.2 Splaying
    4.6 Tree Traversals (Revisited)
    4.7 B-Trees
    4.8 Sets and Maps in the Standard Library
    4.8.1 Sets
    4.8.2 Maps
    4.8.3 Implementation of TreeSet and TreeMap
    4.8.4 An Example That Uses Several Maps
    Summary
    Exercises
    References
    Chapter 5 Hashing
    5.1 General Idea
    5.2 Hash Function
    5.3 Separate Chaining
    5.4 Hash Tables Without Linked Lists
    5.4.1 Linear Probing
    5.4.2 Quadratic Probing
    5.4.3 Double Hashing
    5.5 Rehashing
    5.6 Hash Tables in the Standard Library
    5.7 Hash Tables with Worst-Case O(1) Access
    5.7.1 Perfect Hashing
    5.7.2 Cuckoo Hashing
    5.7.3 Hopscotch Hashing
    5.8 Universal Hashing
    5.9 Extendible Hashing
    Summary
    Exercises
    References
    Chapter 6 Priority Queues (Heaps)
    6.1 Model
    6.2 Simple Implementations
    6.3 Binary Heap
    6.3.1 Structure Property
    6.3.2 Heap-Order Property
    6.3.3 Basic Heap Operations
    6.3.4 Other Heap Operations
    6.4 Applications of Priority Queues
    6.4.1 The Selection Problem
    6.4.2 Event Simulation
    6.5 d-Heaps
    6.6 Leftist Heaps
    6.6.1 Leftist Heap Property
    6.6.2 Leftist Heap Operations
    6.7 Skew Heaps
    6.8 Binomial Queues
    6.8.1 Binomial Queue Structure
    6.8.2 Binomial Queue Operations
    6.8.3 Implementation of Binomial Queues
    6.9 Priority Queues in the Standard Library
    Summary
    Exercises
    References
    Chapter 7 Sorting
    7.1 Preliminaries
    7.2 Insertion Sort
    7.2.1 The Algorithm
    7.2.2 Analysis of Insertion Sort
    7.3 A Lower Bound for Simple Sorting Algorithms
    7.4 Shellsort
    7.4.1 Worst-Case Analysis of Shellsort
    7.5 Heapsort
    7.5.1 Analysis of Heapsort
    7.6 Mergesort
    7.6.1 Analysis of Mergesort
    7.7 Quicksort
    7.7.1 Picking the Pivot
    7.7.2 Partitioning Strategy
    7.7.3 Small Arrays
    7.7.4 Actual Quicksort Routines
    7.7.5 Analysis of Quicksort
    7.7.6 A Linear-Expected-Time Algorithm for Selection
    7.8 A General Lower Bound for Sorting
    7.8.1 Decision Trees
    7.9 Decision-Tree Lower Bounds for Selection Problems
    7.10 Adversary Lower Bounds
    7.11 Linear-Time Sorts: Bucket Sort and Radix Sort
    7.12 External Sorting
    7.12.1 Why We Need New Algorithms
    7.12.2 Model for External Sorting
    7.12.3 The Simple Algorithm
    7.12.4 Multiway Merge
    7.12.5 Polyphase Merge
    7.12.6 Replacement Selection
    Summary
    Exercises
    References
    Chapter 8 The Disjoint Set Class
    8.1 Equivalence Relations
    8.2 The Dynamic Equivalence Problem
    8.3 Basic Data Structure
    8.4 Smart Union Algorithms
    8.5 Path Compression
    8.6 Worst Case for Union-by-Rank and Path Compression
    8.6.1 Slowly Growing Functions
    8.6.2 An Analysis By Recursive Decomposition
    8.6.3 An O( M log * N ) Bound
    8.6.4 An O( M α (M, N) ) Bound
    8.7 An Application
    Summary
    Exercises
    References
    Chapter 9 Graph Algorithms
    9.1 Definitions
    9.1.1 Representation of Graphs
    9.2 Topological Sort
    9.3 Shortest-Path Algorithms
    9.3.1 Unweighted Shortest Paths
    9.3.2 Dijkstra’s Algorithm
    9.3.3 Graphs with Negative Edge Costs
    9.3.4 Acyclic Graphs
    9.3.5 All-Pairs Shortest Path
    9.3.6 Shortest-Path Example
    9.4 Network Flow Problems
    9.4.1 A Simple Maximum-Flow Algorithm
    9.5 Minimum Spanning Tree
    9.5.1 Prim’s Algorithm
    9.5.2 Kruskal’s Algorithm
    9.6 Applications of Depth-First Search
    9.6.1 Undirected Graphs
    9.6.2 Biconnectivity
    9.6.3 Euler Circuits
    9.6.4 Directed Graphs
    9.6.5 Finding Strong Components
    9.7 Introduction to NP-Completeness
    9.7.1 Easy vs. Hard
    9.7.2 The Class NP
    9.7.3 NP-Complete Problems
    Summary
    Exercises
    References
    Chapter 10 Algorithm Design Techniques
    10.1 Greedy Algorithms
    10.1.1 A Simple Scheduling Problem
    10.1.2 Huffman Codes
    10.1.3 Approximate Bin Packing
    10.2 Divide and Conquer
    10.2.1 Running Time of Divide-and-Conquer Algorithms
    10.2.2 Closest-Points Problem
    10.2.3 The Selection Problem
    10.2.4 Theoretical Improvements for Arithmetic Problems
    10.3 Dynamic Programming
    10.3.1 Using a Table Instead of Recursion
    10.3.2 Ordering Matrix Multiplications
    10.3.3 Optimal Binary Search Tree
    10.3.4 All-Pairs Shortest Path
    10.4 Randomized Algorithms
    10.4.1 Random Number Generators
    10.4.2 Skip Lists
    10.4.3 Primality Testing
    10.5 Backtracking Algorithms
    10.5.1 The Turnpike Reconstruction Problem
    10.5.2 Games
    Summary
    Exercises
    References
    Chapter 11 Amortized Analysis
    11.1 An Unrelated Puzzle
    11.2 Binomial Queues
    11.3 Skew Heaps
    11.4 Fibonacci Heaps
    11.4.1 Cutting Nodes in Leftist Heaps
    11.4.2 Lazy Merging for Binomial Queues
    11.4.3 The Fibonacci Heap Operations
    11.4.4 Proof of the Time Bound
    11.5 Splay Trees
    Summary
    Exercises
    References
    Chapter 12 Advanced Data Structures and Implementation
    12.1 Top-Down Splay Trees
    12.2 Red-Black Trees
    12.2.1 Bottom-Up Insertion
    12.2.2 Top-Down Red-Black Trees
    12.2.3 Top-Down Deletion
    12.3 Treaps
    12.4 Suffix Arrays and Suffix Trees
    12.4.1 Suffix Arrays
    12.4.2 Suffix Trees
    12.4.3 Linear-Time Construction of Suffix Arrays and Suffix Trees
    12.5 k-d Trees
    12.6 Pairing Heaps
    Summary
    Exercises
    References
    Index
    A
    B
    C
    D
    E
    F
    G
    H
    I
    J
    K
    L
    M
    N
    O
    P
    Q
    R
    S
    T
    U
    V
    W
    X
    Y
    Z
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    Third Edition Data Structures and Algorithm Analysis in JavaTMTM
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    Third Edition Data Structures and Algorithm Analysis in Java TM Mark A l l en W e i ss Florida International University PEARSON Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London Madrid Milan Munich Paris Montreal Toronto Delhi Mexico City Sao Paulo Sydney Hong Kong Seoul Singapore Taipei Tokyo
    Editorial Director: Marcia Horton Editor-in-Chief: Michael Hirsch Editorial Assistant: Emma Snider Director of Marketing: Patrice Jones Marketing Manager: Yezan Alayan Marketing Coordinator: Kathryn Ferranti Director of Production: Vince O’Brien Managing Editor: Jeff Holcomb Production Project Manager: Kayla Smith-Tarbox Project Manager: Pat Brown Manufacturing Buyer: Pat Brown Art Director: Jayne Conte Cover Designer: Bruce Kenselaar Cover Photo: c De-Kay Dreamstime.com Media Editor: Daniel Sandin Full-Service Project Management: Integra Composition: Integra Printer/Binder: Courier Westford Cover Printer: Lehigh-Phoenix Color/Hagerstown Text Font: Berkeley-Book Copyright c 2012, 2007, 1999 Pearson Education, Inc., publishing as Addison-Wesley. All rights reserved. Printed in the United States of America. This publication is protected by Copyright, and permission should be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or trans- mission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. To obtain permission(s) to use material from this work, please submit a written request to Pearson Education, Inc., Permissions Department, One Lake Street, Upper Saddle River, New Jersey 07458, or you may fax your request to 201-236-3290. Many of the designations by manufacturers and sellers to distinguish their products are claimed as trade- marks. Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed in initial caps or all caps. Library of Congress Cataloging-in-Publication Data Weiss, Mark Allen. Data structures and algorithm analysis in Java / Mark Allen Weiss. – 3rd ed. p. cm. ISBN-13: 978-0-13-257627-7 (alk. paper) ISBN-10: 0-13-257627-9 (alk. paper) 1. Java (Computer program language) 2. Data structures (Computer science) 3. Computer algorithms. QA76.73.J38W448 2012 005.1–dc23 2011035536 I. Title. 15 14 13 12 11—CRW—10 9 8 7 6 5 4 3 2 1 ISBN 10: 0-13-257627-9 ISBN 13: 9780-13-257627-7
    To the love of my life, Jill.
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