Object Oriented Data Structures Using Java 1st Edition by Nell Dale, Daniel T Joyce, Chip Weems ISBN 0763710792 9780763710798

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ISBN 10: 0763710792 
ISBN 13: 9780763710798
Author: Nell Dale, Daniel T Joyce, Chip Weems

This book teaches the classic data structures with an informal, yet rigorous, approach; it includes the appropriate object-oriented concepts and makes use of the appropriate Java constructs.

Object Oriented Data Structures Using Java 1st Table of contents:

• Basic Concepts of Object-Oriented Programming

  • 2.1 Classes and Objects
  • 2.2 Inheritance and Polymorphism
  • 2.3 Abstraction and Encapsulation
  • 2.4 Interfaces and Abstract Classes
  • 2.5 Exception Handling in Java
  • 2.6 Java Collections Framework Overview

• Arrays and Strings in Java

  • 3.1 Introduction to Arrays
  • 3.2 One-Dimensional and Multi-Dimensional Arrays
  • 3.3 Operations on Arrays: Searching, Sorting, Insertion, Deletion
  • 3.4 Working with Strings in Java
  • 3.5 StringBuffer and StringBuilder in Java

• Linked Lists

  • 4.1 Introduction to Linked Lists
  • 4.2 Singly Linked List
  • 4.3 Doubly Linked List
  • 4.4 Circular Linked List
  • 4.5 Implementing Linked Lists Using Java Classes
  • 4.6 Linked List Operations: Insertion, Deletion, Traversal
  • 4.7 Advantages and Disadvantages of Linked Lists

• Stacks and Queues

  • 5.1 Introduction to Stacks
  • 5.2 Stack Operations: Push, Pop, Peek, IsEmpty
  • 5.3 Applications of Stacks: Expression Evaluation, Function Calls
  • 5.4 Introduction to Queues
  • 5.5 Queue Operations: Enqueue, Dequeue, Peek, IsEmpty
  • 5.6 Types of Queues: Circular Queue, Priority Queue, Double-ended Queue (Deque)
  • 5.7 Implementing Stacks and Queues Using Java

• Trees

  • 6.1 Introduction to Trees
  • 6.2 Binary Trees and Binary Search Trees (BST)
  • 6.3 Tree Traversals: Pre-order, In-order, Post-order
  • 6.4 Balanced Trees: AVL Trees
  • 6.5 Red-Black Trees
  • 6.6 Heap Trees: Min-Heap and Max-Heap
  • 6.7 Implementing Trees in Java

• Hashing and Hash Tables

  • 7.1 Introduction to Hashing
  • 7.2 Hash Functions and Collisions
  • 7.3 Hash Tables: Basic Operations and Implementation
  • 7.4 Handling Collisions: Chaining vs. Open Addressing
  • 7.5 Implementing Hash Tables Using Java

• Graphs

  • 8.1 Introduction to Graphs
  • 8.2 Types of Graphs: Directed, Undirected, Weighted
  • 8.3 Graph Representation: Adjacency Matrix, Adjacency List
  • 8.4 Graph Traversals: Depth First Search (DFS), Breadth First Search (BFS)
  • 8.5 Shortest Path Algorithms: Dijkstra’s Algorithm, Bellman-Ford Algorithm
  • 8.6 Minimum Spanning Tree: Prim’s and Kruskal’s Algorithms
  • 8.7 Implementing Graphs in Java

• Sorting Algorithms

  • 9.1 Introduction to Sorting
  • 9.2 Bubble Sort, Selection Sort, and Insertion Sort
  • 9.3 Merge Sort and Quick Sort
  • 9.4 Heap Sort
  • 9.5 Sorting in Java: Using Comparable and Comparator Interfaces
  • 9.6 Time and Space Complexity of Sorting Algorithms

• Searching Algorithms

  • 10.1 Linear Search vs Binary Search
  • 10.2 Binary Search Tree Search Operations
  • 10.3 Hashing as a Searching Technique
  • 10.4 Searching Algorithms in Java
  • 10.5 Time and Space Complexity of Search Algorithms

• Advanced Data Structures

  • 11.1 Tries (Prefix Trees)
  • 11.2 Segment Trees
  • 11.3 B-Trees and B+ Trees
  • 11.4 Self-Balancing Trees: Red-Black Trees, AVL Trees
  • 11.5 Skip Lists
  • 11.6 Implementing Advanced Data Structures Using Java

• Object-Oriented Design Principles for Data Structures

  • 12.1 Principles of Object-Oriented Design
  • 12.2 Design Patterns for Data Structures
  • 12.3 The Role of Encapsulation in Data Structures
  • 12.4 Inheritance and Composition in Data Structures
  • 12.5 Implementing Reusable and Maintainable Data Structures in Java

• Applications of Data Structures

  • 13.1 Real-world Applications of Linked Lists
  • 13.2 Stacks and Queues in Real Applications
  • 13.3 Trees in File Systems and Databases
  • 13.4 Graphs in Social Networks and Routing Algorithms
  • 13.5 Using Data Structures in Software Engineering

• Performance Analysis

  • 14.1 Time and Space Complexity Analysis
  • 14.2 Big-O Notation
  • 14.3 Worst-case, Best-case, and Average-case Analysis
  • 14.4 Profiling Java Code for Performance
  • 14.5 Optimizing Data Structures for Real-World Performance

• Practical Laboratory Exercises

  • 15.1 Exercise 1: Implementing Arrays and Linked Lists
  • 15.2 Exercise 2: Implementing Stacks and Queues
  • 15.3 Exercise 3: Tree Operations and Traversals
  • 15.4 Exercise 4: Graph Traversals and Algorithms
  • 15.5 Exercise 5: Sorting and Searching Algorithms in Java
  • 15.6 Exercise 6: Implementing Advanced Data Structures

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