COR-Matrix

Code Origin Ratio Matrix - Track and analyze how much AI-generated code survives in your codebase over time.

What is COR-Matrix?

COR-Matrix helps development teams understand the real-world impact of AI-generated code by tracking what percentage of originally AI-generated code remains unchanged versus modified or removed during development.

The Problem: Teams using AI coding assistants don't know if the generated code is actually useful long-term or gets rewritten immediately.

The Solution: COR-Matrix captures signatures of AI-generated code as it's written, then analyzes your codebase later to show retention rates and code evolution patterns.

Quick Start

1. Start the API Server

Option A: Using Docker Compose (Recommended)

# Set up environment variables
cp .env.example .env
# Edit .env file with your actual values

# Start the API server with Docker
docker-compose up -d

Option B: Local Development

# Install dependencies
bun install

# Set up environment variables
cp .env.example .env
# Edit .env file with your actual values

# Run database migrations
bun run db:push

# Start the API server
bun run dev:api

The API will be available at http://localhost:3000 with documentation at http://localhost:3000/docs.

2. Track AI-Generated Code (SDK)

Install the client SDK in your project:

npm install @presidio-dev/cor-matrix

Integrate tracking into your development workflow:

import { CorMatrix } from "@presidio-dev/cor-matrix";

const corMatrix = new CorMatrix({
  appName: "my-app",
  baseURL: "http://localhost:3000",
  token: "your-workspace-token",
  workspaceId: "your-workspace-id",
});

// Track AI-generated code as you write it
corMatrix.addCodeOriginRecord({
  code: "console.log('Hello from AI');",
  path: "src/index.ts",
  language: "typescript",
  generatedBy: "copilot",
});

3. Generate Reports (CLI)

Analyze your codebase to see AI code retention:

npx @presidio-dev/cor-matrix report \
  --workspace-id your-workspace-id \
  --project-path /path/to/your/project \
  --api-url http://localhost:3000 \
  --api-token your-workspace-token

Example output:

 COR-Matrix Report
────────────────────────────────────────────────────────────────
Codebase Path:                  /path/to/your/project
Report Time:                    June 1, 2025 at 6:00 PM
Total Lines:                    961 (100%)
AI-Written Lines:               40 of 961 (4.16%)
────────────────────────────────────────────────────────────────

Development

# Database operations
bun run db:generate    # Generate migrations
bun run db:push        # Apply migrations
bun run db:studio      # Open database GUI

# Development
bun run dev:api        # Start API server with hot reload
bun run build:client   # Build client SDK
bun run build:api      # Build API Docker image

Development Environment Setup

Runtime Environment

Setting up Bun

The project primarily uses Bun as the JavaScript runtime. To set up Bun:

# Install Bun
curl -fsSL https://bun.sh/install | bash

# Verify installation
bun --version  # Should display 1.2.15 or newer

Node.js Compatibility

While Bun is the primary development runtime, Node.js is required for some operations:

# Recommended Node.js version
node --version  # Should be v18 or newer

# Installing dependencies with Bun
bun install

Database Setup

The project uses SQLite with Drizzle ORM for data persistence:

1. Database Configuration:

   • Copy .env.example to .env and configure the database settings
   • By default, the application uses a SQLite file database

2. Running Migrations:

   # Apply the latest schema to your database
   bun run db:push
   
   # Generate new migrations when schema changes
   bun run db:generate
   
   # Explore your database with the Drizzle Studio GUI
   bun run db:studio

3. Database Structure:

   • The database schema is defined in TypeScript using Drizzle ORM
   • Migrations are stored in the drizzle directory

Testing

Run integration tests using Vitest:

# Run all integration tests
bun run test:integration

# Run tests in watch mode during development
bun run test:integration:watch

Docker Development

For containerized development:

# Build the API Docker image
bun run build:api

# Run with Docker Compose
docker-compose up -d

# View logs
docker-compose logs -f

Architecture

• API Server: Elysia.js REST API with SQLite database
• SDK: Node.js library for real-time code tracking
• CLI: Command-line tool for codebase analysis
• Database: Stores code signatures and workspace data

Tech Stack

Programming Languages

• TypeScript: The entire project is built using TypeScript, providing strong typing, enhanced IDE support, and improved code quality through compile-time error checking.

Runtime Environments

• Bun: A fast all-in-one JavaScript runtime that serves as the primary runtime environment for the project. Bun is used for running the API server, executing scripts, and managing dependencies.
• Node.js: Used as a complementary runtime environment, particularly for the SDK which is published as an npm package for broader compatibility with Node.js-based projects.

Frameworks

• Elysia.js: A high-performance TypeScript web framework built on Bun that powers the REST API. Elysia.js offers type-safe route definitions, middleware support, and integrated Swagger documentation.

Database Technology

• SQLite: A lightweight, file-based database engine used for local development and embedded deployments.
• Drizzle ORM: A TypeScript-first ORM for SQL databases with a lightweight, relational-focused API. Drizzle handles schema definitions, migrations, and database operations with full type safety.
• Database Migration: The project includes automated schema migrations using drizzle-kit, with commands for generating and applying migrations (db:generate, db:push).

Testing Frameworks

• Vitest: A Vite-based test runner with a Jest-compatible API that provides fast, modern testing capabilities. Used for integration testing the API endpoints and core functionality.
• Testcontainers: Used in integration tests to create isolated Docker container environments for testing database interactions and API functionality.
• Supertest: HTTP assertion library used for testing API endpoints in integration tests.

Containerization and CI/CD

• Docker: The project uses Docker for containerization, with multi-platform support (linux/amd64, linux/arm64). The API server is packaged as a containerized application for easy deployment.
• Docker Compose: Provided as the recommended way to run the API server, handling environment configuration and service orchestration.
• GitHub Actions: Comprehensive CI/CD pipeline that:
  • Runs integration tests on every push to main and rc branches
  • Builds and publishes Docker images to GitHub Container Registry
  • Builds and publishes the SDK package to npm
  • Handles versioning for both Docker images and npm packages
  • Generates build summaries for each workflow run

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Security

For security concerns, please see our Security Policy.