Interview Challenge Simulator

A technical interview tool that goes beyond LeetCode. Instead of abstract puzzles, candidates face a real bug in a real codebase, and are evaluated not only on their ability to fix it, but on how they communicate under pressure.

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Preview

Screenshots

Interviewer Dashboard

Session Selection & Status	Live Candidate Progress Monitoring

Candidate Experience

Stage 1: Coding Challenge	Stage 2: Team Collaboration

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How it works

The interviewer creates a session by selecting a job role. The backend calls the Gemini API to generate a small code snippet(with chosen language by interviewer) with an intentional bug appropriate for that role. The candidate receives a link and has 10 minutes to find the bug, fix it, and explain what went wrong.

If time runs out, or the candidate completes stage 1, a second stage unlocks: a cosmetic Slack-like workspace where the candidate can message the team, ask for help, and demonstrate that they know how to communicate a problem even when they can't solve it alone. The interviewer monitors everything in real time from their dashboard.

When the session ends, all data is permanently deleted.

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Tech stack

• Frontend: React, TypeScript, Tailwind CSS, Monaco Editor
• Backend: C# with ASP.NET Core Web API
• Database: SQL Server with Entity Framework Core
• AI: Google Gemini API

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Getting Started

You can run this project either using Docker (recommended for quick setup) or locally by running the backend and frontend services separately.

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Running with Docker (Recommended)

Docker Compose automatically spins up the database (SQL Server), the backend API, and the frontend web app with a single command.

Prerequisites

• Docker Desktop installed and running.

Setup & Run

1. Configure Environment Variables: Copy the .env.example file in the root directory to .env:

   cp .env.example .env

   Open the .env file and fill in your details:

   • AUTH_PASSWORD: The password you will use to log in to the interviewer dashboard.
   • GEMINI_API_KEY: Your Google Gemini API key (get one for free at aistudio.google.com).

2. Spin up the Containers: In the root directory, run:

   docker compose up --build

3. Access the Application:

   • Interviewer / Candidate Web Client: http://localhost:5173
   • Backend API Docs / Base: http://localhost:5138/api

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Running locally

If you prefer to run the services individually on your machine:

Prerequisites

• .NET 10 SDK
• Node.js (v18+)
• SQL Server (local instance running)
• Google Gemini API key

1. Backend Setup

1. Navigate to the backend directory:

   cd Backend/sim_backend

2. Create an appsettings.Development.json file in Backend/sim_backend/ with the following configuration:

   {
     "ConnectionStrings": {
       "DefaultConnection": "Server=localhost;Database=InterviewChallengeDB;Trusted_Connection=True;TrustServerCertificate=True;"
     },
     "Auth": {
       "Password": "your_password_here"
     },
     "Gemini": {
       "ApiKey": "your_gemini_api_key_here"
     }
   }

3. Apply Entity Framework migrations and start the backend:

   dotnet ef database update
   dotnet run

2. Frontend Setup

1. Navigate to the frontend directory:

   cd Frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

4. Access the interviewer panel at http://localhost:5173 and log in using the password configured in appsettings.Development.json.

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Notes

• appsettings.Development.json and .env are gitignored to prevent sensitive credentials leaking.
• All session data is permanently deleted from the database when the interviewer clicks "End Session" in their dashboard.