Welcome to the "Computer Science Concepts" repository! This repository contains practical challenges that I have written in Python. These challenges are designed to help practicing and improving my knowledge of the Python language, algorithms, time-space complexity (Big O Notation), and various data structures commonly used in programming.
The challenges in this repository cover a range of topics, including:
- Array Reversal: Reverses an array. Time complexity: O(n).
- Palindrome Checker: Checks whether a string is a palindrome. Time complexity: O(n).
- Binary Search: Performs a binary search on a sorted array. Time complexity: O(log n).
- Quick Sort: Sorts an array using the Quick Sort algorithm. Time complexity: O(n log n) on average, O(n^2) in the worst case.
- Hash Table Implementation: Implements a hash table data structure. Time complexity: O(1) on average, O(n) in the worst case.
- Binary Tree Traversal: Performs various traversals on a binary tree. Time complexity: O(n).
The Quick Sort method is a widely used sorting algorithm that follows the divide-and-conquer approach. It has the following time complexity:
- Average case: O(n log n)
- Worst case: O(n^2)
The Quick Sort algorithm has a good average case time complexity and is often used in practice due to its efficiency. However, in the worst case, it can have a quadratic time complexity. Efforts have been made to mitigate this issue by using randomized partitioning or choosing a good pivot element.
- Clone the repository:
git clone https://github.com/your-username/Computer-Science-Concepts.git. - Navigate to the repository:
cd Computer-Science-Concepts. - Open the individual challenge files in your preferred Python editor.
Please, feel free to provide constructive feedback regarding the content of this repository by sending an e-mail.
The code in this repository is available under the MIT License.