📘 Day 1: Introduction to Database Management System (DBMS)

 

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✅ What is a Database?

A Database is an organized collection of data that can be easily accessed, managed, and updated.

🧠 Example: Your college stores data of students — names, roll numbers, marks — in a structured format.

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✅ What is a DBMS?

A Database Management System (DBMS) is software that interacts with users, applications, and the database itself to capture and analyze data.

💡 DBMS Examples:

• MySQL

• Oracle

• PostgreSQL

• MongoDB (NoSQL DB)

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✅ Advantages of DBMS over File System

File System	DBMS
Data Redundancy	Reduced Redundancy
No data sharing	Multi-user support
No data security	High security
Difficult backup	Easy backup & recovery
Complex queries	Easy SQL-based queries

✅ Types of DBMS

Type	Description	Example
Hierarchical	Parent-child	IBM IMS
Network	Graph structure	IDS
Relational	Tables (rows/columns)	MySQL, Oracle
Object-oriented	Stores data as objects	Versant

🧠 MCA Exams usually focus on Relational DBMS (RDBMS).

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✅ Components of DBMS

1. Hardware: Physical devices (server, storage)

2. Software: The DBMS itself (MySQL, etc.)

3. Data: The actual stored data

4. Users:

   • DBA (Database Admin)

   • End Users

   • Application Programmers

5. Procedures: Rules for design & access

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✅ Architecture of DBMS

📊 3-Tier Architecture:

1. External Level: User view

2. Conceptual Level: Logical structure

3. Internal Level: Physical storage

Draw this in exams – it gets full marks!

+---------------------+         <-- External Level (View)
| User 1 / User 2 ... |
+---------------------+
         ↓
+---------------------+         <-- Conceptual Schema
| Logical Structure   |
+---------------------+
         ↓
+---------------------+         <-- Internal Level (Storage)
| Files, Indexes, Data|
+---------------------+

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📝 Day 1 Quick Questions (Important for Exams)

1. What is a DBMS? Explain its advantages.

2. Differentiate between DBMS and File System.

3. Explain 3-tier architecture of DBMS with a diagram.

4. List and describe the types of DBMS.

5. Who are the users of DBMS?

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💻 Mini Practice (Optional)

If you have MySQL installed, try this:

CREATE DATABASE dbms_day1;
USE dbms_day1;

CREATE TABLE student (
    id INT PRIMARY KEY,
    name VARCHAR(100),
    course VARCHAR(50)
);

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✅ Homework (15 mins)

• Revise all notes above

• Draw DBMS architecture diagram in your notebook

• Write down 3 advantages of DBMS

• Prepare answers for the 5 questions above

🎯 MCA DBMS Study Plan for Scoring High in College

We’ll break it down into:

📘 1. Important Theory Topics (Frequently Asked in Exams)

💡 2. Expected Questions from Each Topic

💻 3. Basic SQL Practice (For Viva / Practical Exams)

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📘 1. Important Theory Topics

Unit	Topic	Must-Know Concepts
1	Introduction to DBMS	Definition, advantages, DBMS vs RDBMS, applications
2	Data Models & ER Model	Entity, attributes, relationships, ER diagrams
3	Relational Model	Tuple, attribute, schema, keys (primary, foreign)
4	Relational Algebra	Select, Project, Join, Union, Set Difference
5	SQL Basics	CREATE, INSERT, SELECT, UPDATE, DELETE, WHERE, JOINS
6	Normalization	1NF, 2NF, 3NF, BCNF, functional dependency
7	Transaction Management	ACID properties, commit, rollback
8	Indexing & Storage	B+ trees, hashing, file organization

💡 2. Important Questions to Study

✅ Short Questions:

• What is DBMS? List its advantages.

• Define primary and foreign keys with examples.

• What is normalization?

✅ Long Questions (most scoring):

• Draw and explain the architecture of DBMS.

• Explain ER model with an example and convert it to tables.

• What are the types of keys in DBMS? Explain with example.

• Write and explain different SQL commands with examples.

• Explain all normal forms with suitable examples.

• What is a transaction? Explain ACID properties.

🧠 Tip: Draw diagrams in theory exams — ER diagrams, DBMS architecture, relational schema — these fetch full marks.

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💻 3. Basic SQL Commands (Exam Viva Focus)

-- Create a table
CREATE TABLE student (
    id INT PRIMARY KEY,
    name VARCHAR(100),
    course VARCHAR(50)
);

-- Insert data
INSERT INTO student VALUES (1, 'Adarsh', 'MCA');

-- View table
SELECT * FROM student;

-- Update a record
UPDATE student SET course = 'MCA Part 2' WHERE id = 1;

-- Delete a record
DELETE FROM student WHERE id = 1;

💡 Learn:

• INNER JOIN

• GROUP BY and HAVING

• Subqueries (simple SELECT inside WHERE)

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📅 Weekly Exam-Focused Study Plan (Short-Term Revision)

Day	Focus Area
Day 1	DBMS Intro + Architecture + Advantages
Day 2	ER Model + Diagram Practice
Day 3	Keys + Relational Model
Day 4	Relational Algebra + Set operations
Day 5	SQL Basics (DDL, DML, DQL) + Practice
Day 6	Normalization (1NF to BCNF)
Day 7	Transactions + Indexing + Storage

📝 Bonus: Exam Writing Tips

• Write definitions in your own words.

• Underlined keywords: DBMS, Primary Key, ACID, etc.

• Use diagrams: ER model, Architecture.

• Give examples always — even for short answers.

• Neat formatting = easy marks!

✅ Day 4: Sorting Algorithms (Basic to Intermediate)

🎯 Goals for Today

• Understand how sorting works and why it’s needed

• Learn and implement:

  • Bubble Sort

  • Selection Sort

  • Insertion Sort

• Analyze time & space complexities

• Practice beginner sorting problems

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📘 1. Why Sorting Matters

Sorting helps:

• Optimize searching (e.g., binary search)

• Solve problems like duplicates, frequency, etc.

• Prepare data for algorithms like two pointers, greedy, divide & conquer, etc.

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🔁 2. Sorting Algorithms

🔹 Bubble Sort

Repeatedly swap adjacent elements if they are in the wrong order.

public class BubbleSort {
    public static void bubbleSort(int[] arr) {
        int n = arr.length;
        for (int i = 0; i < n - 1; i++) {
            boolean swapped = false;
            for (int j = 0; j < n - i - 1; j++) {
                if (arr[j] > arr[j + 1]) {
                    // swap
                    int temp = arr[j];
                    arr[j] = arr[j + 1];
                    arr[j + 1] = temp;
                    swapped = true;
                }
            }
            if (!swapped) break;
        }
    }
}

• Time Complexity: Worst → O(n²), Best → O(n) (already sorted)

• Space: O(1)

---

🔹 Selection Sort

Find the minimum element and put it at the beginning.

public class SelectionSort {
    public static void selectionSort(int[] arr) {
        int n = arr.length;
        for (int i = 0; i < n - 1; i++) {
            int minIndex = i;
            for (int j = i + 1; j < n; j++) {
                if (arr[j] < arr[minIndex]) {
                    minIndex = j;
                }
            }
            // swap
            int temp = arr[i];
            arr[i] = arr[minIndex];
            arr[minIndex] = temp;
        }
    }
}

• Time Complexity: Always O(n²)

• Space: O(1)

---

🔹 Insertion Sort

Build the sorted array one element at a time by inserting elements at the correct position.

public class InsertionSort {
    public static void insertionSort(int[] arr) {
        for (int i = 1; i < arr.length; i++) {
            int current = arr[i];
            int j = i - 1;

            while (j >= 0 && arr[j] > current) {
                arr[j + 1] = arr[j];
                j--;
            }
            arr[j + 1] = current;
        }
    }
}

• Time Complexity: Best → O(n), Worst → O(n²)

• Space: O(1)

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🧠 3. Sorting Algorithm Comparison Table

Algorithm	Time Complexity (Best / Avg / Worst)	Space	Stable?
Bubble Sort	O(n) / O(n²) / O(n²)	O(1)	✅
Selection Sort	O(n²) / O(n²) / O(n²)	O(1)	❌
Insertion Sort	O(n) / O(n²) / O(n²)	O(1)	✅

🔍 4. Practice Problems

Try these:

• Sort an array of 0s, 1s, and 2s (Dutch National Flag)

• Check if an array is sorted and rotated

• Count the number of swaps required to sort the array

• Sort a nearly sorted (k-sorted) array

You can also implement a custom comparator or reverse order sort (forward-thinking Java practice).

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📚 Homework for Day 4

✅ Implement all three sorting algorithms
✅ Solve 2 sorting-based problems from LeetCode:

• Sort Colors

• Check if Array Is Sorted and Rotated

Would you like solutions for these 2 LeetCode problems?

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⏭️ What’s Coming on Day 5:

• Advanced Sorting: Merge Sort, Quick Sort

• Time Complexity Analysis

• Recursion involved in sorting

🚀 DSA with C – Day 3: Bubble Sort & Binary Search

 

🎯 Goal:

• Learn Bubble Sort and sort arrays.

• Understand how Binary Search works.

• Compare Linear vs Binary Search.

• Practice problems on sorted arrays.

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🧠 Theory

✅ Bubble Sort:

• Repeatedly compares adjacent elements and swaps them if they’re in the wrong order.

• Worst-case time complexity: O(n²)

• Best-case (already sorted): O(n) with optimization

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👨‍💻 Bubble Sort in C

#include <stdio.h>

int main() {
    int arr[100], n, i, j, temp;

    printf("Enter number of elements: ");
    scanf("%d", &n);
    printf("Enter %d elements:\n", n);
    for (i = 0; i < n; i++)
        scanf("%d", &arr[i]);

    // Bubble Sort
    for (i = 0; i < n - 1; i++) {
        int swapped = 0;
        for (j = 0; j < n - i - 1; j++) {
            if (arr[j] > arr[j + 1]) {
                // Swap
                temp = arr[j];
                arr[j] = arr[j + 1];
                arr[j + 1] = temp;
                swapped = 1;
            }
        }
        if (swapped == 0)
            break; // Already sorted
    }

    printf("Sorted array:\n");
    for (i = 0; i < n; i++)
        printf("%d ", arr[i]);

    return 0;
}

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✅ Binary Search:

• Efficient searching technique on sorted arrays.

• Time Complexity: O(log n)

• Repeatedly divide the array and compare with middle element.

---

👨‍💻 Binary Search in C

#include <stdio.h>

int binarySearch(int arr[], int n, int key) {
    int low = 0, high = n - 1, mid;

    while (low <= high) {
        mid = (low + high) / 2;

        if (arr[mid] == key)
            return mid;
        else if (arr[mid] < key)
            low = mid + 1;
        else
            high = mid - 1;
    }

    return -1; // Not found
}

int main() {
    int arr[100], n, key;

    printf("Enter number of elements: ");
    scanf("%d", &n);
    printf("Enter %d sorted elements:\n", n);
    for (int i = 0; i < n; i++)
        scanf("%d", &arr[i]);

    printf("Enter element to search: ");
    scanf("%d", &key);

    int result = binarySearch(arr, n, key);
    if (result == -1)
        printf("Element not found.\n");
    else
        printf("Element found at index %d.\n", result);

    return 0;
}

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🔁 Linear vs Binary Search

Feature	Linear Search	Binary Search
Time Complexity	O(n)	O(log n)
Sorted Array Required	❌ No	✅ Yes
Speed	Slower	Faster for large data
Approach	Scan all elements	Divide & Conquer

🧪 Practice Problems:

1. Sort an array using Bubble Sort in descending order.

2. Count how many swaps were done during Bubble Sort.

3. Use Binary Search to find the number of occurrences of a given element.

4. If not found in Binary Search, return where it should be inserted.

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📘 Homework for Day 3:

• Implement recursive Binary Search.

• Write a program that first sorts using Bubble Sort and then searches using Binary Search.

• LeetCode problem suggestion: Search Insert Position

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📅 Day 3 Summary

• ✅ Learned Bubble Sort (with optimization)

• ✅ Implemented Binary Search (iterative)

• ✅ Practiced comparing search algorithms

✅ Solution Implement Both Linear and Binary Search Day 3 DSA with Java

🔹 Linear Search in Java

public class LinearSearch {
    public static int linearSearch(int[] arr, int key) {
        for (int i = 0; i < arr.length; i++) {
            if (arr[i] == key) return i;
        }
        return -1; // Not found
    }

    public static void main(String[] args) {
        int[] arr = {5, 3, 8, 2, 9};
        int key = 8;
        int index = linearSearch(arr, key);
        System.out.println("Element found at index: " + index);
    }
}

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🔹 Binary Search in Java (Iterative)

public class BinarySearch {
    public static int binarySearch(int[] arr, int key) {
        int start = 0, end = arr.length - 1;
        while (start <= end) {
            int mid = start + (end - start) / 2;
            if (arr[mid] == key) return mid;
            else if (arr[mid] < key) start = mid + 1;
            else end = mid - 1;
        }
        return -1;
    }

    public static void main(String[] args) {
        int[] arr = {1, 3, 5, 7, 9};
        int key = 5;
        int index = binarySearch(arr, key);
        System.out.println("Element found at index: " + index);
    }
}

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✅ 2. LeetCode Problems

🔸 Search Insert Position

Problem: Return the index if the target is found. If not, return the index where it would be inserted.

public class SearchInsertPosition {
    public static int searchInsert(int[] nums, int target) {
        int low = 0, high = nums.length - 1;
        while (low <= high) {
            int mid = low + (high - low) / 2;
            if (nums[mid] == target) return mid;
            else if (nums[mid] < target) low = mid + 1;
            else high = mid - 1;
        }
        return low;
    }

    public static void main(String[] args) {
        int[] nums = {1, 3, 5, 6};
        int target = 2;
        System.out.println("Insert position: " + searchInsert(nums, target));
    }
}

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🔸 First Bad Version

Assume isBadVersion(version) API exists.

public class FirstBadVersion {
    static int bad = 4; // Let's assume version 4 is the first bad version

    public static boolean isBadVersion(int version) {
        return version >= bad;
    }

    public static int firstBadVersion(int n) {
        int low = 1, high = n;
        while (low < high) {
            int mid = low + (high - low) / 2;
            if (isBadVersion(mid)) high = mid;
            else low = mid + 1;
        }
        return low;
    }

    public static void main(String[] args) {
        System.out.println("First bad version: " + firstBadVersion(10));
    }
}

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🌱 3. Explore: Lower Bound & Upper Bound

These are binary search variants often used in competitive programming.

🔸 Lower Bound (First element ≥ target)

public static int lowerBound(int[] arr, int target) {
    int low = 0, high = arr.length;
    while (low < high) {
        int mid = low + (high - low) / 2;
        if (arr[mid] < target) low = mid + 1;
        else high = mid;
    }
    return low; // returns the index
}

🔸 Upper Bound (First element > target)

public static int upperBound(int[] arr, int target) {
    int low = 0, high = arr.length;
    while (low < high) {
        int mid = low + (high - low) / 2;
        if (arr[mid] <= target) low = mid + 1;
        else high = mid;
    }
    return low; // returns the index
}

You can test both with:

int[] arr = {1, 3, 3, 5, 7};
System.out.println("Lower Bound of 3: " + lowerBound(arr, 3)); // Output: 1
System.out.println("Upper Bound of 3: " + upperBound(arr, 3)); // Output: 3

🚀 Day 3: Searching Algorithms in Java

🎯 Goals:

• Understand Linear Search and Binary Search

• Learn when and how to use each

• Solve real interview problems using searching techniques

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🔍 1. Linear Search

📘 Definition:

Linearly checks each element one by one. Used when the array is unsorted.

✅ Code Example:

public static int linearSearch(int[] arr, int key) {
    for (int i = 0; i < arr.length; i++) {
        if (arr[i] == key) return i;
    }
    return -1; // Not found
}

---

🧠 2. Binary Search

📘 Definition:

Used on sorted arrays. It divides the search space in half each time — O(log N) time complexity.

✅ Code (Iterative Approach):

public static int binarySearch(int[] arr, int key) {
    int start = 0, end = arr.length - 1;
    while (start <= end) {
        int mid = start + (end - start) / 2;

        if (arr[mid] == key) return mid;
        else if (arr[mid] < key) start = mid + 1;
        else end = mid - 1;
    }
    return -1;
}

✅ Code (Recursive Approach):

public static int binarySearchRec(int[] arr, int key, int start, int end) {
    if (start > end) return -1;

    int mid = start + (end - start) / 2;
    if (arr[mid] == key) return mid;
    else if (arr[mid] < key) return binarySearchRec(arr, key, mid + 1, end);
    else return binarySearchRec(arr, key, start, mid - 1);
}

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💡 3. Binary Search Use Cases

• Search in sorted array

• Find first/last occurrence of an element

• Search in rotated sorted arrays

• Peak elements in mountain arrays

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✍️ 4. Practice Problems

🔹 Write functions to:

• Find first and last occurrence of an element (e.g. in sorted duplicates)

• Count how many times a number appears in sorted array

• Search in a rotated sorted array

• Find square root using binary search (approximate to floor)

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🔥 5. BONUS – Search in 2D Matrix

🔹 Use binary search logic on 2D:

public static boolean searchMatrix(int[][] matrix, int target) {
    int rows = matrix.length;
    int cols = matrix[0].length;
    int low = 0, high = rows * cols - 1;

    while (low <= high) {
        int mid = low + (high - low) / 2;
        int value = matrix[mid / cols][mid % cols];

        if (value == target) return true;
        else if (value < target) low = mid + 1;
        else high = mid - 1;
    }
    return false;
}

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📚 Homework for Day 3:

• Implement both linear and binary search

• Solve 2 problems from LeetCode:

  • Search Insert Position

  • First Bad Version

• Explore: Lower Bound, Upper Bound (optional but forward-thinking)

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⏭️ What’s Coming on Day 4?

• Sorting Algorithms: Bubble, Selection, Insertion (with time/space analysis)

🧪 Practice Problems Answer Day 2 DSA with C

 

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✅ 1. Find Maximum and Minimum in an Array

#include <stdio.h>

int main() {
    int n, i;
    int arr[100], max, min;

    printf("Enter number of elements: ");
    scanf("%d", &n);

    printf("Enter %d elements:\n", n);
    for (i = 0; i < n; i++) {
        scanf("%d", &arr[i]);
    }

    max = min = arr[0];

    for (i = 1; i < n; i++) {
        if (arr[i] > max)
            max = arr[i];
        if (arr[i] < min)
            min = arr[i];
    }

    printf("Maximum: %d\n", max);
    printf("Minimum: %d\n", min);

    return 0;
}

---

✅ 2. Count Occurrences of a Given Number

#include <stdio.h>

int main() {
    int n, x, count = 0;
    int arr[100];

    printf("Enter number of elements: ");
    scanf("%d", &n);

    printf("Enter %d elements:\n", n);
    for (int i = 0; i < n; i++) {
        scanf("%d", &arr[i]);
    }

    printf("Enter number to count: ");
    scanf("%d", &x);

    for (int i = 0; i < n; i++) {
        if (arr[i] == x)
            count++;
    }

    printf("Number %d appears %d time(s).\n", x, count);

    return 0;
}

---

✅ 3. Reverse an Array

#include <stdio.h>

int main() {
    int n, arr[100];

    printf("Enter number of elements: ");
    scanf("%d", &n);

    printf("Enter %d elements:\n", n);
    for (int i = 0; i < n; i++) {
        scanf("%d", &arr[i]);
    }

    printf("Reversed array:\n");
    for (int i = n - 1; i >= 0; i--) {
        printf("%d ", arr[i]);
    }

    return 0;
}

---

📘 Homework

---

✅ 4. Copy One Array to Another

#include <stdio.h>

int main() {
    int n, arr1[100], arr2[100];

    printf("Enter number of elements: ");
    scanf("%d", &n);

    printf("Enter %d elements for arr1:\n", n);
    for (int i = 0; i < n; i++) {
        scanf("%d", &arr1[i]);
        arr2[i] = arr1[i];  // Copying
    }

    printf("Copied array (arr2):\n");
    for (int i = 0; i < n; i++) {
        printf("%d ", arr2[i]);
    }

    return 0;
}

---

✅ 5. Merge Two Arrays

#include <stdio.h>

int main() {
    int arr1[50], arr2[50], merged[100];
    int n1, n2, i;

    printf("Enter number of elements in arr1: ");
    scanf("%d", &n1);
    printf("Enter %d elements for arr1:\n", n1);
    for (i = 0; i < n1; i++)
        scanf("%d", &arr1[i]);

    printf("Enter number of elements in arr2: ");
    scanf("%d", &n2);
    printf("Enter %d elements for arr2:\n", n2);
    for (i = 0; i < n2; i++)
        scanf("%d", &arr2[i]);

    for (i = 0; i < n1; i++)
        merged[i] = arr1[i];
    for (i = 0; i < n2; i++)
        merged[n1 + i] = arr2[i];

    printf("Merged array:\n");
    for (i = 0; i < n1 + n2; i++)
        printf("%d ", merged[i]);

    return 0;
}

🚀 DSA with C – Day 2: Arrays & Linear Search

 

🎯 Goal:

• Understand arrays in C.

• Learn how to use loops with arrays.

• Implement Linear Search algorithm.

• Practice multiple array-based programs.

---

🧠 Theory: What is an Array?

• An array is a collection of elements stored in contiguous memory.

• All elements must be of the same type.

• Indexing starts from 0 in C.

🔧 Declaration and Initialization

int arr[5];             // Declaration
int arr[5] = {1, 2, 3, 4, 5};  // Initialization

---

👨‍💻 Basic Program: Input & Output in Arrays

#include <stdio.h>

int main() {
    int arr[5];
    printf("Enter 5 numbers:\n");
    for (int i = 0; i < 5; i++) {
        scanf("%d", &arr[i]);
    }

    printf("You entered:\n");
    for (int i = 0; i < 5; i++) {
        printf("%d ", arr[i]);
    }
    return 0;
}

---

🔍 Linear Search in C

➕ Problem: Given an array and a number x, find if x exists in the array.

✅ Code:

#include <stdio.h>

int main() {
    int arr[100], n, x, found = 0;
    printf("Enter number of elements: ");
    scanf("%d", &n);

    printf("Enter %d elements:\n", n);
    for (int i = 0; i < n; i++)
        scanf("%d", &arr[i]);

    printf("Enter element to search: ");
    scanf("%d", &x);

    for (int i = 0; i < n; i++) {
        if (arr[i] == x) {
            printf("Element found at index %d\n", i);
            found = 1;
            break;
        }
    }

    if (!found)
        printf("Element not found\n");

    return 0;
}

🧠 Time Complexity:

• Best case: O(1)

• Worst case: O(n)

---

🧪 Practice Problems:

1. Find the maximum and minimum element in an array.

2. Count how many times a given number appears in the array.

3. Reverse an array.

---

📘 Homework for Day 2:

• Write a program to copy one array to another.

• Write a program to merge two arrays.

• Try solving one problem from LeetCode Easy using arrays (optional but forward-thinking!).

---

📅 Day 2 Summary

• ✅ Learned arrays

• ✅ Implemented Linear Search

• ✅ Practiced I/O and traversal

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🧭 Tomorrow: Sorting (Bubble Sort) + Binary Search

Would you like me to create a GitHub repo or planner to track your DSA progress daily?