Part 1 explored why AI is a game-changer for debugging, especially for computer science students. Now that you know the why, let’s dive into the how.
AI isn’t just good at catching bugs, it’s great at teaching you how to catch them too. Whether you’re dealing with a frustrating syntax error or trying to understand a weird output, AI can help. Here are five smart and practical ways to use AI as your go-to debugging assistant.
Get Clear Explanations for Error Messages
You’ve seen them: TypeError: unsupported operand type(s), Segmentation fault (core dumped), SyntaxError: unexpected EOF while parsing
Error messages can be cryptic and intimidating especially if you’re still learning the language. AI tools like ChatGPT and Replit Ghostwriter can help by translating these into plain English.
Example Prompt:
“Why am I getting this error in my Python code?” (Paste code and error message)
You don’t just fix the issue, you understand why it happened. That’s key to becoming a better programmer.
Ask for Fix Suggestions
AI tools don’t just explain problems, it often provides line-by-line corrections or even refactor your entire block of code for clarity and performance.
Example Prompt:
“Can you help me fix this function so it returns the right result?” (Include function + test case)
Tools to Try:
- GitHub Copilot for live suggestions in VS Code
- ChatGPT for full-code analysis
Pro Tip: Compare the AI’s fix to your original code. Try to understand what changed and why.
Understand What Your Code Actually Does
Sometimes the bug isn’t an error, it’s the unexpected behavior. AI can walk you through what each part of your code is doing.
Example Prompt:
“Can you explain what this recursive function is doing?” (Paste function)
This is especially helpful when:
- Reviewing your own older code
- Collaborating on group projects
- Learning new concepts (like recursion or sorting algorithms)
Generate Test Cases
Want to catch bugs before they happen? Use AI to write test cases that check your functions with different inputs.
Example Prompt:
“Write a few unit tests for this function using pytest.” (Paste function)
You’ll not only find edge cases you didn’t think of but also learn how to write better test coverage which is a must-have skill for any developer.
Use AI in Real-Time as You Code
The best debugging happens before the bug hits “Run.” With tools like Copilot you get AI support as you write your code.
- Autocomplete suggestions based on context
- Warnings when something looks off
- Inline fixes for small mistakes
It’s like having access to a coding mentor who is available 24-7.
AI Debugging Toolbox
Now that you’ve got practical ways to use AI while coding, stay tuned for Part 3 that will cover:
- How to choose the right AI tools for you
- Tips for crafting better prompts
- How to avoid common pitfalls
- Using AI to boost your problem-solving skills
You’re not just writing better code, you’re learning to think like a developer. And AI is here to help you every step of the way.
Written by: Ivanna Gutierrez
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