Data Structures and Problem Solving Using Java 4th edition by Mark Allen Weiss ISBN 0321541405 978-0321541406

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ISBN 10: 0321541405
ISBN 13:  978-0321541406
Author: Mark Allen Weiss 

Data Structures and Problem Solving Using Java takes a practical and unique approach to data structures that separates interface from implementation. It is suitable for the second or third programming course.

This book provides a practical introduction to data structures with an emphasis on abstract thinking and problem solving, as well as the use of Java. It does this through what remains a unique approach that clearly separates each data structure’s interface (how to use a data structure) from its implementation (how to actually program that structure). Parts I (Tour of Java), II (Algorithms and Building Blocks), and III (Applications) lay the groundwork by discussing basic concepts and tools and providing some practical examples, while Part IV (Implementations) focuses on implementation of data structures. This forces the reader to think about the functionality of the data structures before the hash table is implemented.

The Fourth Edition features many new updates as well as new exercises.

Data Structures and Problem Solving Using Java 4th Table of contents:

Part 1: Introduction to Java and Problem Solving

Chapter 1: Introduction to Java and Problem Solving
1.1. Overview of Java
1.2. Java Development Environment
1.3. Basic Java Syntax and Structure
1.4. Problem Solving and Algorithm Development
1.5. Problem-Solving Techniques
1.6. Debugging and Testing in Java

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Part 2: Fundamentals of Data Structures

Chapter 2: Arrays and Strings
2.1. Introduction to Arrays
2.2. One-Dimensional Arrays
2.3. Multi-Dimensional Arrays
2.4. Java Strings
2.5. Arrays and Strings Applications
2.6. The Java Collections Framework

Chapter 3: Linked Lists
3.1. Introduction to Linked Lists
3.2. Singly Linked Lists
3.3. Doubly Linked Lists
3.4. Circular Linked Lists
3.5. Linked List Operations and Applications
3.6. Implementing Linked Lists in Java

Chapter 4: Stacks and Queues
4.1. Stack Abstract Data Type
4.2. Implementing Stacks
4.3. Queue Abstract Data Type
4.4. Implementing Queues
4.5. Applications of Stacks and Queues
4.6. Priority Queues

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Part 3: Trees

Chapter 5: Binary Trees
5.1. Introduction to Binary Trees
5.2. Binary Tree Traversals
5.3. Binary Tree Applications
5.4. C++ Implementations of Binary Trees

Chapter 6: Binary Search Trees
6.1. Introduction to Binary Search Trees (BST)
6.2. Operations on BSTs
6.3. Insertion, Deletion, and Searching
6.4. Self-Balancing Binary Search Trees (AVL Trees)
6.5. C++ Implementation of Binary Search Trees

Chapter 7: Balanced Trees
7.1. AVL Trees
7.2. Red-Black Trees
7.3. Splay Trees
7.4. B-Trees
7.5. Tree Implementations in Java

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Part 4: Graphs

Chapter 8: Graphs
8.1. Introduction to Graphs
8.2. Graph Representations: Adjacency Matrix and List
8.3. Graph Traversals: Depth-First Search and Breadth-First Search
8.4. Shortest Path Algorithms
8.5. Minimum Spanning Trees
8.6. Applications of Graphs

Chapter 9: Advanced Graph Algorithms
9.1. Topological Sorting
9.2. Strongly Connected Components
9.3. Dijkstra’s Algorithm
9.4. Bellman-Ford Algorithm
9.5. Floyd-Warshall Algorithm
9.6. Network Flow Problems

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Part 5: Sorting and Searching

Chapter 10: Sorting Algorithms
10.1. Introduction to Sorting
10.2. Bubble Sort
10.3. Selection Sort
10.4. Insertion Sort
10.5. Merge Sort
10.6. Quick Sort
10.7. Heap Sort
10.8. Comparison of Sorting Algorithms
10.9. Sorting Algorithms in Java

Chapter 11: Searching Algorithms
11.1. Linear Search
11.2. Binary Search
11.3. Hashing and Hash Tables
11.4. Collision Resolution Strategies
11.5. Hash Functions
11.6. Searching in Java

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Part 6: Advanced Data Structures

Chapter 12: Advanced Data Structures
12.1. Heaps
12.2. Priority Queues
12.3. Disjoint Set Data Structures
12.4. Tries and Prefix Trees
12.5. B-Trees and Multiway Trees
12.6. Fibonacci Heaps

Chapter 13: Algorithm Design Techniques
13.1. Divide and Conquer
13.2. Dynamic Programming
13.3. Greedy Algorithms
13.4. Backtracking Algorithms
13.5. Branch and Bound
13.6. Randomized Algorithms

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Part 7: Problem Solving with Data Structures

Chapter 14: Problem Solving with Data Structures
14.1. Problem-Solving Strategies
14.2. Divide and Conquer Approach
14.3. Dynamic Programming Approach
14.4. Greedy Algorithms Approach
14.5. Case Studies in Problem Solving

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