Introduction

What is Data structure ?

Data Structures and Algorithms (DSA) are the building blocks of programming and software development. They help you write efficient, optimized, and scalable code. Whether you’re building a simple app or a complex system, understanding DSA is essential for solving real-world problems.

A Data Structure is a way of organizing, storing, and managing data so that it can be used efficiently.

Imagine a bookshelf in a library:

• If books are arranged properly (e.g., by category or alphabetically), it’s easier to find them.
• If books are placed randomly, it will take longer to find a specific book.

Similarly, in programming, data structures help in organizing data efficiently so that operations like searching, inserting, and deleting data can be performed quickly.

Classification of Data structure

Need of Data Structure

• Modification is Easy.
• It requires less time.
• Save storage memory space.
• Data representation is easy.
• Easy access to the large database.

What are Algorithm ?

Algorithms are step-by-step procedures for solving a problem or performing a task. They define the logic and steps needed to manipulate data stored in data structures.

Example of an Algorithm in Real Life

Imagine you are making tea. The steps can be written as an algorithm:

1. Boil water.
2. Add tea leaves.
3. Let it steep for 2 minutes.
4. Add sugar and milk.
5. Stir well.
6. Pour into a cup and serve.

Each step must be followed in order to get the correct result. Similarly, in programming, an algorithm follows a sequence of steps to solve a problem.

Example of an Algorithm in Programming

Let’s write an algorithm to find the sum of two numbers:

1. Start
2. Take two numbers as input (A and B).
3. Add A and B.
4. Display the result.
5. Stop

Example in Code

#include <stdio.h>

int main() {
    int A, B, sum;
    printf("Enter two numbers: ");
    scanf("%d %d", &A, &B);
    sum = A + B;
    printf("Sum is: %d", sum);
    return 0;
}

Why Learn DSA ?

1. Efficiency: Write programs that run faster and use less memory.
2. Problem-Solving: Develop the ability to break down complex problems into smaller, manageable parts.
3. Career Growth: DSA is a key topic in coding interviews for top tech companies.
4. Foundation for Advanced Topics: Essential for learning machine learning, artificial intelligence, and more.

Application of DSA

1. Search Engines: Algorithms like PageRank power Google.
2. Social Networks: Graphs are used to represent connections.
3. Gaming: Pathfinding algorithms are used in game AI.
4. Databases: Indexing and searching use hash tables and trees.