🔄 Code Migration Agent

AI-Powered Legacy Application Modernization Platform

Automating the transformation of legacy .NET (C#) applications into modern Java projects using intelligent code analysis, Retrieval-Augmented Generation (RAG), validation pipelines, security analysis, and automated project generation.

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📖 Overview

Legacy software modernization is one of the most challenging problems in enterprise software engineering. Large-scale applications often contain years of accumulated business logic, making manual migration slow, expensive, and highly error-prone.

Code Migration Agent is an AI-powered software modernization platform designed to automate the migration of legacy .NET (C#) applications into modern Java implementations. Instead of functioning as a simple code converter, the system follows an intelligent multi-stage migration pipeline that combines deterministic transformation rules with Retrieval-Augmented Generation (RAG), validation, security analysis, and automated project generation.

The result is a structured, transparent, and reliable migration workflow that preserves application logic while reducing manual engineering effort.

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🌍 Why This Project?

Organizations worldwide continue to rely on legacy software systems that are costly to maintain and difficult to modernize.

Migrating these systems manually often requires extensive engineering effort, deep framework expertise, and significant quality assurance.

This project demonstrates how AI-assisted software modernization can accelerate migration workflows by combining deterministic translation with contextual AI reasoning, automated validation, and security analysis to produce production-ready Java projects.

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🛠️ Technology Stack

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✨ Core Capabilities

🚀 Module	Description
🔁 Intelligent Code Migration	Converts legacy .NET (C#) source code into equivalent Java implementations while preserving business logic.
🧠 Migration Planning	Analyzes project structure and generates an optimized migration workflow.
📚 Retrieval-Augmented Generation	Retrieves migration knowledge, coding standards, and best practices using Milvus Lite.
✅ Validation Pipeline	Performs syntax validation, migration verification, and iterative self-correction.
🔒 Security Analysis	Detects exposed credentials, insecure coding patterns, and potential vulnerabilities.
📦 Project Builder	Automatically generates complete Java project structures and downloadable ZIP archives.
📝 Audit Reporting	Produces detailed migration logs and execution reports for traceability.

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🏗️ System Architecture

             Legacy .NET Application
                      │
                      ▼
              Source Code Analysis
                      │
                      ▼
             Migration Planning Engine
                      │
                      ▼
        Rule-Based Translation Pipeline
                      │
                      ▼
     Retrieval-Augmented Generation (RAG)
                      │
                      ▼
          Multi-Pass Validation Engine
                      │
                      ▼
           Static Security Analysis
                      │
                      ▼
          Java Project Generation
                      │
                      ▼
        Downloadable Project & Reports

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🔄 Migration Workflow

Upload .NET Source Code
            │
            ▼
Project Structure Analysis
            │
            ▼
Migration Planning
            │
            ▼
Rule-Based Code Translation
            │
            ▼
Knowledge Retrieval (RAG)
            │
            ▼
Java Code Generation
            │
            ▼
Validation Pipeline
            │
            ▼
Security Analysis
            │
            ▼
Project Packaging
            │
            ▼
Download Java Project

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⚙️ Engineering Design

🧩 Rule-Based Translation

The migration engine separates deterministic language conversion from AI-generated contextual reasoning.

This ensures:

• Consistent syntax mapping
• Framework annotation conversion
• Data type transformations
• Predictable migration behavior

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📚 Retrieval-Augmented Generation (RAG)

Rather than asking the LLM to generate code without context, the system retrieves relevant migration knowledge from a Milvus Lite vector database.

Retrieved knowledge includes:

• Migration guidelines
• Coding standards
• Framework documentation
• Enterprise best practices

This approach improves consistency while reducing hallucinations.

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🛡️ Validation & Security

Every generated file passes through multiple validation stages before project generation.

The pipeline performs:

• Syntax validation
• Migration verification
• Static security analysis
• Credential detection
• Unsafe coding pattern detection

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📂 Project Structure

Code-Migration-Agent/

│
├── agent/
├── audit/
├── config/
├── data/
├── rag/
├── rules/
├── sample_inputs/
├── security/
├── target_outputs/
├── validation/
│
├── app.py
├── cli.py
├── requirements.txt
└── README.md

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🚀 Getting Started

Clone Repository

git clone https://github.com/himani-malik/Code-Migration-Agent.git

cd Code-Migration-Agent

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Install Dependencies

pip install -r requirements.txt

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Build the Vector Database

python cli.py index

This initializes the local Milvus Lite vector database used for Retrieval-Augmented Generation.

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Run the Application

python app.py

or

python cli.py

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📁 Sample Migration

Input

TodoController.cs

⬇️

Generated Output

TodoController.java

The generated Java project is packaged and made available for download after successful validation.

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🚀 Future Roadmap

• 🌍 Multi-language migration support
• 🧠 AST-based semantic code transformation
• 🔌 IDE Plugin Integration
• ⚡ Incremental repository migration
• 🐳 Dockerized deployment
• ☁️ Cloud-native execution
• 🔄 CI/CD integration
• 👨‍💻 Human-in-the-loop code review
• 🤖 Multi-LLM provider support

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🎓 Engineering Highlights

This project demonstrates practical experience with:

• Agentic AI Systems
• Software Modernization
• Legacy Application Migration
• Retrieval-Augmented Generation (RAG)
• LangChain
• Vector Databases
• Static Code Analysis
• Security Validation
• Python Backend Development
• Software Architecture
• Intelligent Developer Tools

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👩‍💻 Author

Himani Malik

B.Tech Computer Science (AI & Machine Learning)

Passionate about building intelligent software systems, developer productivity tools, and AI-powered software modernization platforms that combine machine learning with practical software engineering.