Data Structures and Algorithms

This repository contains implementations of common algorithms in C++. Below is a brief overview of each algorithm, its time complexity, and typical usage scenarios.

Sorting Algorithms

1. Bubble Sort

   • Time Complexity: O(n²)
   • Usage: Simple but inefficient, used for small datasets or educational purposes.

2. Selection Sort

   • Time Complexity: O(n²)
   • Usage: Better than bubble sort for small datasets, useful for learning purposes.

3. Quick Sort

   • Time Complexity: O(n log n) on average
   • Usage: Efficient for large datasets; performance may degrade with bad pivot choices.

4. Merge Sort

   • Time Complexity: O(n log n)
   • Usage: Stable and consistent, ideal for large datasets where stability is required.

5. Insertion Sort

   • Time Complexity: O(n²)
   • Usage: Efficient for small datasets and nearly sorted data.

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Problem-Solving

1. Two Sum Problem

   • Description: Find two numbers that add up to a target value.
   • Time Complexity: O(n)
   • Usage: Common problem in coding interviews.

2. Counter Problem

   • Description: Count occurrences of elements in an array.
   • Time Complexity: O(n)
   • Usage: Useful for frequency counting.

3. Remove Duplicates

   • Description: Remove duplicates from a sorted array.
   • Time Complexity: O(n)
   • Usage: Simplifies an array by removing duplicate values.

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Credits

Developed by Muhammad Saif.