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1
1
Pakistan
2+ years of experience
Hi, I am a computer science student, with a strong passion for learning and hands-on experience in full-stack web development. I’ve built a solid foundation in the MERN stack [MongoDB, Express.js, React.js, and Node.js] and continue to sharpen my skills through real-world projects and collaborative experiences. Lately, I’ve been diving into data structures and algorithms to strengthen my problem-solving abilities. I’m also passionate about tech communities and love participating in hackathons and coding competitions to challenge myself and grow. Feel free to reach out. Let's connect and grow together!

AutoTest Agent is an AI-powered developer tool that takes a module of code and its intended use case (as text), then automatically generates and runs unit/integration tests. It leverages the multi-agent, deep-context, and LLM capabilities of Trae AI IDE to accelerate the testing process, ensuring better code coverage and developer productivity. ✅ Problem Statement: Many developers skip writing unit tests due to time constraints or lack of expertise. This leads to: Bugs in production Poor code quality Difficult code reviews and refactoring 💡 Solution: We provide a tool that: Accepts code modules (Python) Accepts a requirement/use-case description Uses AI agents to: Analyze the code Understand the use case Generate unit test cases Optionally run tests and show results 🔧 Key Features: 📥 Code Upload/Input – Users can upload or paste their Python code module 🗒️ Use Case Input – Short description of the intended functionality 🤖 AI Test Generator – AI agent generates test cases using pytest or unittest ▶️ Test Runner – (Optional) Run tests and return pass/fail results 💬 Feedback Loop – Users can edit/refine tests or regenerate 🧰 Technology Stack: Language – Python Test Framework – pytest or unittest AI Models – GPT-4o, Claude 3.5, Gemini 2.5 via Trae UI (optional) – Streamlit / CLI Version Control – GitHub 🤖 How Trae AI IDE is Used: Built custom AI agents using editable prompt templates Agents deeply understand code modules using context-aware capabilities Generated test cases with LLM support from Trae (GPT-4o, Claude) Leveraged Trae's real-time preview and one-click execution for faster iterations
15 Jun 2025