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 ## Use of Generative AI — Guidelines and Requirements
 Generative AI tools (such as ChatGPT, GitHub Copilot, Gemini, etc.) are widely available and may be used **responsibly** in this course as **learning assistants**. The goal of assignments and projects is not only to produce a working program, but to demonstrate your **understanding of programming concepts** and your ability to explain and modify your own code.
 For this reason, the use of generative AI is **allowed but regulated**.
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 ### 1. Acceptable Uses of Generative AI
 You may use generative AI in ways that **support learning**, including:
 - Explaining C++ concepts (e.g. loops, arrays, pointers, structs)
 - Helping you understand compiler or runtime errors
 - Suggesting ideas or approaches in **plain language**
 - Assisting with debugging **after you have attempted the problem yourself**
 - Improving code readability, comments, or naming
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 ### 2 Unacceptable Uses of Generative AI
 You may **not** use generative AI to:
 - Generate the full project or major parts of it
 - Design the overall architecture of the program
 - Write core logic that you do not fully understand
 - Copy and submit AI-generated code without modification
 - Replace your own reasoning, problem-solving, or debugging effort
 Submitting code that you cannot explain or modify will be treated as **plagiarism**, regardless of whether AI was disclosed.
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 ### 3. Best Practices for Using AI Effectively
 If you choose to use AI, the following practices are strongly recommended:
 - **Try first**: Attempt the problem yourself before asking AI
 - **Ask focused questions**:  
    Instead of “write the code”, ask “why does this loop not work?”
 - **Work in small pieces**:  
    Use AI for specific concepts, not entire features
 - **Rewrite in your own way**:  
    Never submit code exactly as produced by AI
 - **Verify and test**:  
    Always compile, run, and test AI-assisted code
 Using AI as a **tutor**, not as a **code generator**, leads to better learning and better results.
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 ### 4. Evaluation and Accountability
 During grading or oral evaluation, you may be asked to:
 - Explain parts of your code
 - Justify design decisions
 - Make small modifications to your program
 Your grade is based on **understanding and ownership**, not on how quickly the program was completed.