A tool for generating and testing "dry runs" (tricky C++ code snippets often asked in exams by universities like FAST) in an isolated Docker environment.
This project provides a system for:
- Generating challenging C++ code snippets that test understanding of tricky language concepts
- Running the code snippets safely in a virtual execution environment using Docker
- Automated testing and verification (as the outputs are fed back to a reasoning LLM)
- Focuses on tricky C++ concepts like:
- sizeof() and datatype size edge cases
- Order of operations (e.g., x++ + x++)
- Conditional statement edge cases
- Loop patterns
- Pointer manipulation and const correctness among many others asked by FAST in courses like Programming Fundamentals (PF) and Object Oriented Programming (OOP).
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Prerequisites:
- Python 3.x
- Docker
- Required Python packages (see requirements)
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Environment Variables:
- Generate an API Key from Google AI Studio
- Create a
.env
file with:GOOGLE_API_KEY=your_api_key_here
Run the main script:
python main.py