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Data Structures and Algorithms

Begin with complexity analysis, then learn common data structures, sorting and searching algorithms, and techniques such as divide and conquer, greedy algorithms, dynamic programming, and pattern matching.

Table of Contents

Chapter 1: Computational Complexity Theory

1.1 Time and Space Complexity

1.2 Recurrence Relations

Chapter 2: Arrays

2.1 Search Algorithms

2.2 Array Insertion and Deletion

2.3 Implement a Generic Array

Chapter 3: Linked Lists

3.1 Types of Linked Lists

3.2 Finding Nodes

3.3 Singly Linked List Operations

3.4 Implement a Generic Singly Linked List

3.5 Doubly Linked List Operations

3.6 Implement a Generic Doubly Linked List

Chapter 4: Stacks

4.2 Implement a Generic Stack

4.3 Parentheses Matching

4.4 Expression Evaluation

Chapter 5: Queues

5.2 Implement a Generic Queue

Chapter 6: Hash Tables

6.1 Hash Tables and Hash Functions

6.2 Constructing Hash Functions

6.3 Collisions and Open Addressing

6.4 Chaining and Performance

Chapter 7: Divide and Conquer

7.1 Divide and Conquer

7.2 Big Integer Arithmetic

7.3 Fast Exponentiation

7.4 Matrix Multiplication

Chapter 8: Sorting Algorithms

8.1 Sorting Algorithms

8.2 Bubble Sort

8.3 Selection Sort

8.4 Insertion Sort

8.8 Counting Sort

8.9 Bucket Sort

8.10 Radix Sort

Chapter 9: Trees

9.2 Binary Tree Traversal

9.3 Binary Search Trees

9.4 Implement a Binary Search Tree

9.5 Huffman Trees

Chapter 10: Graphs

10.2 Graph Representation

10.3 Graph Traversal

10.4 Connected Graphs

10.5 Shortest Paths

10.6 Minimum Spanning Trees

10.7 Topological Sort

Chapter 11: Greedy Algorithms

11.1 Greedy Algorithms

11.2 Distributing Cookies

11.3 Greedy Coin Change

11.4 Fractional Knapsack

11.5 Limitations of Greedy Algorithms

Chapter 12: Dynamic Programming

12.1 Dynamic Programming

12.2 Coin Change

12.3 Path Problems

12.5 0-1 Knapsack

Chapter 13: Pattern Matching

SUITABLE AUDIENCE

Beginning programmers studying data structures and algorithms systematically for the first time.

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