Data Structures and Algorithms in Java, 6ed, ISV (An Indian Adaptation)

Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, Subhasish Banerjee

ISBN: 9789354247934

INR 849

Description

Data Structures and Algorithms in Java offers a comprehensive, definitive introduction to data structures and algorithms, including their design, analysis, and implementation in Java. The contents of the book are organized to provide a pedagogical path that starts with the basics of Java programming and object-oriented design and foundational techniques such as algorithm analysis and recursion. The book then presents fundamental data structures, such as arrays, linked lists, stacks, queues, trees, heaps, maps, hash tables, search trees, and graphs, concluding with a discussion on searching and sorting algorithms and memory management. The book incorporates a host of pedagogical features, including illustrations, code fragments, and end-of-chapter exercises.

 

1 Introduction to Java

1.1 Preliminaries

1.2 Objects and Classes

1.3 Special Types

1.4 Java Expressions

1.5 Control Flow

1.6 Input and Output

1.7 Java Packages

1.8 Writing a Java Program

 

2 Object-Oriented Programming

2.1 Goals, Principles, and Patterns

2.2 Inheritance

2.3 Interfaces and Abstract Classes

2.4 Exception

2.5 Casting and Generics

2.6 Nested Classes

 

3 Introduction to Data Structures and Algorithms

3.1 Data Structures

3.2 Empirical Analysis

3.2.1 Moving Beyond Experimental Analysis

3.3 Common Mathematical Functions

3.4 Asymptotic Notations

 

4 Arrays and Linked Lists

4.1 Practical Uses of Arrays

4.2 Singly Linked Lists

4.3 Circularly Linked Lists

4.4 Doubly Linked Lists

4.5 Testing for Equality

4.6 Copying Data Structures

 

5 Recursion

5.1 Foundations of Recursion

5.2 Recursive Analysis

5.3 Applications of Recursion

5.4 Using Recursion

5.5 Pitfalls of Recursion

 

6 Stacks and Queues

6.1 Stacks

6.2 Queues

6.3 Double-Ended Queues

 

7 List Abstractions

7.1 The List ADT

7.2 Array-Based Lists

7.3 Position-Based Lists

7.4 Iterators

7.5 The Collections Framework

 

8 Trees

8.1 Trees Definitions and Properties

8.2 Binary Trees

8.3 Tree Representations

8.4 Tree Traversal Algorithms

 

9 Priority Queues and Heaps

9.1 The Priority Queue Abstract Data Type

9.2 Implementing a Priority Queue

9.3 Heaps

9.4 Sorting with a Priority Queue

9.5 Adaptable Priority Queues

 

10 Maps, Hash Tables, and Skip Lists

10.1 The Map Abstract Data Type

10.2 Hashing

10.3 The Sorted Map Abstract Data Type

10.4 Skip Lists

10.5 Sets, Multisets, and Multimaps

 

11 Search Trees

11.1 Binary Search Trees

11.2 Balanced Search Trees

11.3 AVL Trees

11.4 (2, 4) Trees

11.5 Red-Black Trees

11.6 Splay Trees

 

12 Graphs

12.1 Graphs

12.2 Data Structures for Graphs

12.3 Graph Traversals

12.4 Transitive Closure

12.5 Directed Acyclic Graphs

12.6 Shortest Paths

12.7 Minimum Spanning Trees

 

13 Strings and Dynamic Programming

13.1 Preliminaries

13.2 Pattern-Matching Algorithms

13.3 Tries

13.4 Text Compression and the Greedy Method

13.5 Dynamic Programming

 

14 Sorting and Selection

14.1 Merge-Sort

14.2 Quick-Sort

14.3 Studying Sorting through an Algorithmic Lens

14.4 Comparing Sorting Algorithms

14.5 Selection

 

15 Additional Topics

15.1 Memory Management

15.2 Memory Hierarchies and Caching

15.3 External Searching and B-Trees

15.4 Binomial Heap

15.5 External-Memory Sorting

15.6 Range Trees

 

Exercises

Multiple Choice Questions

Chapter Notes

Answer Key

Appendix A: Useful Mathematical Facts

Bibliography

Index

 

 

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