JustBigO-Fun

JustBigO-Fun is an ASP.NET Core 9.0 MVC platform for algorithmic challenges, inspired by sites like LeetCode.

🎥 Demo (screencast): https://youtu.be/4bKce7Ch55Y

📄 The application's technical documentation (features, tech stack, run instructions) is in the Project Documentation section at the end of this README.

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MDS Evaluation — AI-Driven Software Development Process (Component B)

This section maps each evaluation-rubric item to the corresponding artifacts and evidence in the repository. Every item below involved the use of AI tools (Gemini web, Cursor, Gemini CLI, Claude Code) — details in the dedicated report.

1. User stories (min. 10) & backlog creation — 2 pts

The user stories and backlog were created and managed in Jira, formulated and refined with AI (Gemini web) in the standard format ("As a user, I want… so that…"), together with their acceptance criteria.

Jira board (screenshots):

2. Diagrams (UML, component architecture, workflows) — 1 pt

The architecture, component, and workflow diagrams (e.g., the Reflexion loop, the sandbox execution flow) were generated and clarified with AI assistance.

• 📐 Diagrams: docs/DIAGRAMS.md

3. Source control with git (branching, merge/rebase, pull requests, min. 5 commits/student) — 1 pt

Development was done on feature branches (feature/generic-executor-metrics, fix/admin-area-overhaul, Transpilare, Indicii_US12_US13, etc.), with merges, conflict resolution, and pull requests (#4–#19). AI was used to draft commit/PR messages and to resolve merge conflicts.

• 🔗 Pull requests: PRs link
• 🔗 Commit history: commits link

4. Automated tests (including agent evals) — 2 pts

The test suite in JustBigO(Fun).Tests/ covers Controllers, Models, Hubs, and Services. It includes agent evals (AI/CodeTranslatorAgentTests.cs, GeminiHintGeneratorTests.cs, GeminiRefactoringSuggestionGeneratorTests.cs) that verify the structural integrity of AI-generated responses.

• 🧪 Tests: JustBigO(Fun).Tests/

5. Bug reporting and resolution via pull request — 1 pt

Real bugs identified and fixed via PR with AI assistance (diagnosis + fix), e.g.: "No redirect to login page" and "Grey text on dark background" (PR #17), fixing tests after resource-limit changes, and stopping the AI query after a timeout.

• 🐛 Bug + fix (PR): bug/PR link

6. CI/CD pipeline — 1 pt

The pipeline is configured in GitHub Actions and was generated with AI based on the project structure:

• CI (build job, runs on every push/PR): restore → build → run tests on .NET 9.

• CD (publish job, runs only on push to main, after CI passes): dotnet publish in Release mode and uploads the deployable build as a downloadable artifact.

• ⚙️ Workflow: .github/workflows/dotnet-ci.yml

7. Report on the use of AI tools — 2 pts

A detailed report on the AI tools used by each team member and across each development phase.

• 📄 Report: docs/AI_USAGE_REPORT.md

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Project Documentation

It provides a full-stack environment for users to browse coding problems, submit solutions, and have them validated against test cases.

Key Features

• Problem Library: Browse a collection of algorithmic challenges with difficulty levels, tags, and detailed descriptions.
• Solution Submission: Submit C#, Python, Java, and C++ code for evaluation.
• AI Transpiler & Mentor: Features an integrated local AI Agent (Llama 3.2) that can seamlessly translate code between languages and provide hints. The AI uses an autonomous "Reflexion" loop to pre-compile and fix its own code before displaying it.
• Automated Testing: Integrated Docker-based code execution sandbox that runs user submissions and AI drafts against predefined test cases in isolated environments.
• Admin Dashboard: Secure area for managing problems, including CRUD operations and batch uploading test cases (.in/.out files).
• Identity & RBAC: Complete authentication system with role-based access control for users and administrators.

Tech Stack

• Backend: .NET 9.0, ASP.NET Core MVC, C#, SignalR
• Database: SQL Server with Entity Framework Core
• Authentication: ASP.NET Core Identity
• Containerization: Docker (Code Execution Sandbox)
• Local AI Engine: Semantic Kernel & Ollama (Llama 3.2)
• Frontend: Razor Views, Bootstrap, Vanilla CSS, Monaco Editor

Getting Started

Prerequisites

To run this project locally, you must have the following installed and running:

• .NET 9 SDK
• SQL Server (LocalDB supported)
• Docker Desktop (Must be running in the background)
• Ollama (Must be installed for the local AI agent)

Setup Instructions

1. Clone the repository:

   git clone [https://github.com/your-username/JustBigO-Fun.git](https://github.com/your-username/JustBigO-Fun.git)
   cd JustBigO-Fun

2. Build the Docker Execution Sandbox: The application requires a specific Docker image to compile user and AI code. Ensure Docker Desktop is running, then execute this command in the project root:

   docker build -f Runner.Dockerfile -t justbigo-runner:latest .

3. Download the AI Model: The AI transpilation engine relies on the Llama 3.2 model. Run this command to download it to your local machine (this may take a few minutes depending on your internet connection):

   ollama run llama3.2

   (Note: You can close the Ollama chat prompt once the download finishes, but the Ollama app must remain running in your system tray).

4. Configure Database: Update the connection string in JustBigO(Fun)/appsettings.json if you are not using the default LocalDB instance.

5. Restore & Run:

   dotnet restore
   dotnet run --project "JustBigO(Fun)"

   Note: Database migrations and initial data seeding (Problems & Admin user) occur automatically on the first run.

Default Credentials

• Admin Email: [email protected]
• Admin Password: Admin123!

Project Structure

• JustBigO(Fun)/Controllers/: MVC controllers including a dedicated Admin area for problem management.
• JustBigO(Fun)/Hubs/: SignalR hubs for real-time AI code streaming.
• JustBigO(Fun)/Models/: Domain entities like Problem, Submission, and ProblemTest.
• JustBigO(Fun)/Services/: Business logic, specifically the ICodeExecutor (Docker Sandbox) and ICodeTranslatorAgent (AI).
• JustBigO(Fun)/Data/: EF Core context and seeders (ProblemSeeder, AdminSeeder).
• JustBigO(Fun)/Views/: Razor views for the public interface and administrative tools.

Development Conventions

• Surgical Updates: Follow existing patterns for adding new features or fixing bugs.
• Validation: Use Data Annotations for model validation.
• Security: Decorate administrative actions with [Authorize(Roles = AdminSeeder.AdminRole)].
• Testing: New features should be accompanied by verification logic.