Developed an AI-driven solution to automate the migration of legacy code from Delphi, COBOL, and VB to modern technologies such as C and Java, significantly reducing manual effort and errors. It utilizes machine learning models like Deep Q-learning and Natural Language Understanding (NLU) to analyze and translate legacy code snippets. The application also features a chatbot powered by GPT-3 API to assist users with code documentation and queries.
- Automated Legacy Code Migration – Converts legacy code (e.g., Delphi, COBOL, VB) to modern languages (e.g., Java, C).
- Machine Learning-Based Analysis – Uses Deep Q-learning and NLU to improve translation accuracy.
- Chatbot Integration – Powered by GPT-3 API, it helps with code documentation and user queries.
- User-Friendly Interface – Built with React.js and Tailwind CSS.
- Backend Server – Implemented using Flask for seamless API interactions.
- React.js
- Tailwind CSS
- Flask
- Deep Q-learning
- Natural Language Understanding (NLU)
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Clone the repository:
git clone https://github.com/Sumith-2003/Legacy-Code-Migration.git cd Legacy-Code-Migration
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Install frontend dependencies:
cd project npm install npm run dev
The frontend should now be running at
http://localhost:5173
. -
Install backend dependencies:
cd backend pip install -r requirements.txt python app.py
The backend should now be running at
http://localhost:5000
.
- Upload or paste legacy code into the interface.
- Select the target programming language for migration.
- The AI-powered system will analyze and convert the code.
- Use the chatbot for documentation and code-related queries.
- Support for additional programming languages.
- Improved AI model accuracy for complex code migrations.
- Integration with cloud services for scalable processing.
This project is open-source and available under the MIT License.
🚀 Contributions & Issues
Feel free to fork this repository, raise pull requests, or report issues!
For any queries, contact Sumith.