Quickstart Guide for Local Development

This guide walks you through setting up ARViSAN for local development. The easiest way to run ARViSAN is via Docker, but manual setup with Neo4j is also supported.

✅ 1. Pre-requisites

You need one of the following setups:

Alternatively, Local Neo4j Setup

📦 2. Clone the ARViSAN Repositories

First, create a working directory and clone the repositories:

mkdir Arvisan
cd Arvisan

git clone https://github.com/Software-Analytics-Visualisation-Team/arvisan-backend.git
git clone https://github.com/Software-Analytics-Visualisation-Team/arvisan-frontend.git
git clone https://github.com/Software-Analytics-Visualisation-Team/arvisan-dependency-parser.git

⚙️ 3. Set Up Docker or Neo4j

  1. Copy the docker-compose.yml and docker-compose.dev.yml files from arvisan-backend to the parent Arvisan/ folder:
cp arvisan-backend/docker-compose*.yml .

This places the Docker setup at the root where all services can be orchestrated.

Neo4j Manual Setup

  1. Start Neo4j Desktop.
  2. Create a new local database (e.g., named arvisan-db).
  3. In Plugins, install and enable the APOC plugin.
  4. Start the database and take note of:
    • Bolt URL (e.g., bolt://localhost:7687)
    • Username (default: neo4j)
    • Password (set during database creation)

🏃 4. Running ARViSAN

4A. Run with Docker

In the Arvisan folder (where the compose files are), run:

docker-compose -p Arvisan-dev -f docker-compose.yml -f docker-compose.dev.yml up watch

This will:

  • Build and start the backend, frontend, and Neo4j services.
  • Mount code for live development.
  • Automatically reload on file changes.

4B. Run Locally without Docker

  1. Make sure your Neo4j database is running (with APOC plugin enabled).
  2. Start the backend:
cd arvisan-backend
npm install
npm run dev
  1. In a new terminal, start the frontend:
cd ../arvisan-frontend
npm install
npm run dev

You now have:

  • Backend server running (typically on localhost:3000)
  • Frontend UI running (typically on localhost:5173)

🧪 Done!

You’re now running ARViSAN locally. Navigate to localhost:5173 and login with the credentials (by default test_user, test_password). You can parse source code using the dependency parser and upload the generated graph to explore it through the ARViSAN UI.