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AlgoSortIt:Sorting Algorithm Visualizer

🗂 Table of Contents

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📄 Overview

The Sorting Algorithm Visualizer is a web application designed to provide users with an interactive way to visualize and understand various sorting algorithms. By visually representing the process of sorting, this tool helps users grasp how these algorithms function step-by-step and identify their characteristics. It serves as an educational aid, enabling learners and developers to determine the most suitable sorting algorithm for specific scenarios.


🔗 Objectives

The objectives of this project are:

Details 🔴 Visualization of Sorting Algorithms: Display the operations of popular sorting algorithms in real-time, illustrating how they manipulate data during execution.

🔵 Educational Aid: Enhance understanding of sorting techniques by showcasing their mechanics, strengths, and weaknesses in a visually intuitive manner.

🟣 Practical Insights: Help users choose the most appropriate sorting algorithm based on the dataset or problem requirements by comparing the performance of different algorithms.

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🔑 Key Features

The following are the key features of the project:

🟡 Interactive UI to choose and compare different sorting algorithms.

🟢 Step-by-step animations for popular sorting algorithms like:

 *Bubble Sort
 
 *Quick Sort
 
 *Merge Sort
 
 *Insertion Sort
 
 *Selection Sort

🟠 Adjustable input size and speed of visualization for custom scenarios.

🔵 Insights into time complexity, space complexity, and real-world applications for each algorithm.

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Usage

  1. Launch the web application in your browser.

  2. Select a sorting algorithm from the provided list.

  3. Configure input parameters such as:

    *Array size

    *Visualization speed

  4. Start the visualization to observe the algorithm in action.

  5. Review the provided details about the algorithm's performance and characteristics.


Technologies Used

*Frontend: HTML, CSS, JavaScript

*Backend (if applicable): Node.js

*APIs/Frameworks: Firebase

*Security Tools: HTTPS, user authentication, encryption libraries


👥 Team

The following individuals will be working on this project:

ELOPRE, JAKE MAXIM O.

GENIL, GEMMA ROSE L.

MONTOYA, RAM GREGGOR

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