Algorithm Visualization Tool – use any programming language you may see fit for the project

Testing is Required, I would like the test results in pictures please.

Algorithm Visualization Tool

Objective:The Algorithm Visualization Tool aims to provide an educational platform where users can visualize and understand various algorithms through interactive animations and step-by-step explanations. This tool can be integrated into an Integrated Development Environment (IDE) like Visual Studio Code or can be a standalone web application.

Core Features:

1. Visual Representation of Algorithms:Visualize the execution of various algorithms such as sorting (e.g., Quick Sort, Merge Sort), searching (e.g., Binary Search), and graph algorithms (e.g., Dijkstra’s Algorithm, Depth-First Search).Display step-by-step execution to help users follow the algorithm’s logic.
2. Explanatory Notes:Provide detailed explanations of each step in the algorithm, highlighting key operations and decisions.Include educational insights into the algorithm’s working principles and real-world applications.
3. User Input and Interaction:Allow users to input their own data sets for visualization.Enable users to control the execution speed and step through the algorithm manually.
4. Performance Metrics and Complexity Analysis:Display time and space complexity for each algorithm.Compare the performance of different algorithms on the same data set.
5. Optional Animation:Use animations to make the visualization more engaging and intuitive. (This part can be optional depending on development resources and expertise).

Technology Stack:

1. Frontend:HTML5/CSS3: For creating the user interface.JavaScript/TypeScript: For implementing the logic and interactivity.React.js (optional): To create a more dynamic and responsive UI.
2. Visualization Library:D3.js: A powerful library for creating complex data visualizations.Canvas API or SVG: For rendering the visual elements of the algorithms.
3. Backend (optional for more advanced features):Node.js: To handle server-side logic if needed.Express.js: For creating API endpoints if the tool needs to fetch data from a server.
4. IDE Integration (if applicable):VS Code Extension API: For integrating the tool into Visual Studio Code.IntelliJ Platform SDK: For integrating the tool into IntelliJ IDEA.

Development Plan:

1. Setup Development Environment:Install Node.js and npm for managing dependencies.Set up a development environment with the chosen frontend framework (React.js, plain HTML/CSS/JS).
2. Create Basic UI:Design a user-friendly interface with input fields for user data, control buttons for execution, and a display area for visualizations.
3. Implement Core Algorithms:Start by implementing a few basic algorithms (e.g., Bubble Sort, Binary Search) in JavaScript.Create functions to visualize the steps of these algorithms using D3.js or Canvas API.
4. Add Explanatory Notes and Controls:Implement a side panel or tooltip feature that provides explanations for each step.Add controls for users to play, pause, and step through the algorithm manually.
5. Performance Metrics and Analysis:Implement functions to calculate and display the time and space complexity of each algorithm.Provide a comparison feature to visualize the performance of different algorithms on the same data set.
6. Optional Animation:Enhance the visualizations with smooth animations to illustrate the algorithm’s operations more clearly.Use libraries like GSAP (GreenSock Animation Platform) if needed.
7. Testing and Iteration:Conduct thorough testing to ensure the tool works correctly with various data sets and edge cases.Gather feedback from users and make iterative improvements based on their suggestions.
8. IDE Integration (if applicable):Use the VS Code Extension API to package the tool as an extension for Visual Studio Code.Implement necessary commands and user interface components to integrate the tool seamlessly into the IDE.