How to Debug Code Using ChatGPT
Debugging is an essential part of programming, as it helps in identifying and fixing errors in the code. However, the process of debugging can be time-consuming and challenging, especially when dealing with complex code. But with the help of ChatGPT, a large language model trained by OpenAI, debugging can be made much more manageable and efficient. In this article, we will discuss how to debug code using the correct ChatGPT prompt.

ChatGPT is an AI language model trained to generate human-like responses to a variety of prompts. It is capable of understanding natural language and can generate text that is grammatically correct and contextually relevant. The model has been trained on a large corpus of text, which makes it an excellent tool for debugging code.
Specify The Programming Language
The first step is specifying the programming language you want to debug code in. For example, you can say:
Generate Python code to print “Hello World!”
ChatGPT will generate the correct code:
print(“Hello World!”)
Ask Open-Ended Questions
Post open-ended questions about your code to get ChatGPT to explain its logic step-by-step. For example, ask:
Walk me through how this code works.
ChatGPT will describe the purpose of variables, functions, and loops in the code. This helps you identify any errors or inefficient logic. I once asked ChatGPT to walk me through a machine learning model code I had written in Python. ChatGPT looked at each line and told me that my hyperparameter values weren't best for the data. This helped me make the model work better.
Request Specific Lines of Code
If you spot an issue in a few lines of code, ask ChatGPT to re-generate just those lines. For example, say:
Please rewrite lines 15–20 in this code.
ChatGPT will provide alternative code just for the lines you specified. This precise editing prevents disturbance of the working code. I used this prompt to fix a bug in just a few lines of my Python code. ChatGPT rewrote those lines with the correct syntax and logic to fix the bug.
Provide Sample Inputs and Outputs
When debugging, it's often necessary to test code with different inputs and make sure it gives the expected results. You can give ChatGPT inputs and ask it to provide the corresponding outputs. For example:
If you input 50 into this code, what should be the output?
ChatGPT will run the code with an input of 50 and tell you what the output value should be. You can then check if your code is producing the same output. This prompt is invaluable when debugging machine learning models. I provided sample inputs to my model, and ChatGPT told me the expected predictions or recommendations, allowing me to quickly detect any issues.
There are many ways to debug your code, and I would like to share what I am using for my debugging. Here are some specific points you could include in a prompt for debugging Python or SQL code, presented in a tabular format. To use ChatGPT for debugging, you need to follow these steps:
Step 1: Identify the Error
The first step in debugging code using ChatGPT is to identify the error. You need to understand the error message and how it relates to the code. Once you have identified the error, you can move on to the next step.
Step 2: Generate a Prompt
The second step is to generate a prompt that will help ChatGPT understand the error. The prompt should be specific and provide enough information for ChatGPT to generate a relevant response. For example, if you have a syntax error in your code, you can generate a prompt like “What is the syntax error in my code?”
Step 3: Generate a Response
Once you have generated a prompt, you can input it into ChatGPT and generate a response. ChatGPT will analyze the prompt and generate a response that is relevant to the error. The response may include suggestions for fixing the error, or it may provide a more detailed explanation of the error.
Step 4: Implement the Solution
After generating a response, you can implement the solution into your code. You may need to modify your code based on the suggestions provided by ChatGPT. Once you have made the necessary changes, you can test your code to ensure that the error has been fixed.
Example — Debugging Python code
I want you to be a Python programmer, here is a piece of Python code containing {problem} — {insert code snippet} — I am getting the following error {insert error}. What is the reason for the bug?
Make sure to fill in each of these points with specific details relevant to your project and the issue you are encountering. By including these details in a clear and organized way, you can help make sure that the person you're asking for help will have all the information they need to help you debug your code.
|Introduction |Hello, I am working on a project in [insert project details]. |
|--------------------|------------------------------------------------------------------------------------------------------------------------|
|Specific Task |I am currently having trouble with a particular piece of code that involves [insert specific task/operation]. |
|Programming Language|I am using Python/SQL. |
|Error Message |When I run my code, I am encountering the following error message: [insert error message]. |
|Debugging Steps |I have tried [insert things you have tried to debug the code], but I am still unable to resolve the issue. |
|Code Snippet |Here is the relevant section of my code: [insert relevant code snippet]. |
|Request for Help |I would greatly appreciate it if you could help me debug this code and provide any insights or suggestions you may have.|

| Technique | Prompt |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Isolation | I have narrowed down the error to [insert specific lines of code]. Can you help me understand what's causing the error in this section? |
| Debugging Statements | I have included print statements in my code to help debug, but I am not getting the expected output. Can you help me understand what's going wrong? |
| Syntax Checking | I have checked my syntax and can't find any issues, but I am still getting an error. Can you help me understand what else could be causing the problem? |
| Data Verification | I suspect that there may be an issue with the input data I am using. Can you help me verify that my data is correctly formatted? |
| Version Testing | I have checked my code on different versions of Python/SQL, but the error persists. Can you help me understand what else could be causing the problem? |
| Memory Optimization | I am running out of memory when running my code. Can you help me optimize my code to reduce memory usage? |
| Query Optimization | I am getting unexpected results from my SQL query. Can you help me optimize my query to return the expected results? |
| Documentation Review | I have encountered an error that is not in the documentation for this library. Can you help me understand what's causing the error? |
| Thread Safety | I am encountering an issue that seems to be related to multithreading or multiprocessing. Can you help me debug my code to ensure that it is thread-safe? |
| Configuration Issues | I am encountering an issue that only occurs in certain environments or configurations. Can you help me understand how to configure my environment to resolve the issue? |

| Technique | Prompt |
| ------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Bottleneck Identification | Can you help me identify any potential performance bottlenecks in this section of [Python/SQL] code? I suspect that it may be causing slowdowns in my application. |
| Query Optimization | I am encountering slow query times when running this [SQL] query. Can you help me optimize the query to improve performance? |
| Memory Optimization | I am running into memory issues when running this [Python/SQL] code. Can you help me identify ways to reduce memory usage? |
| Runtime Optimization | I am experiencing slow runtime when executing this [Python/SQL] code. Can you help me identify any areas where I can improve runtime performance? |
| Code Streamlining | I suspect that there may be unnecessary iterations or redundancy in this [Python/SQL] code. Can you help me identify ways to streamline the code and improve performance? |
| Database Schema Optimization | Can you help me identify any database schema issues that may be causing slow query times when running this [SQL] query? |
| Parallelization Optimization | I am encountering slowdowns in my application when running this [Python/SQL] code. Can you help me identify any parallelization opportunities to improve performance? |
| Subquery Optimization | I suspect that there may be inefficient or redundant subqueries in this [SQL] query. Can you help me optimize the query to improve performance? |
| I/O Optimization | I am encountering slow runtime when executing this [Python/SQL] code due to excessive I/O operations. Can you help me identify ways to reduce I/O overhead and improve performance? |
| Algorithm/Data Structure Optimization | Can you help me identify any areas in this [Python/SQL] code where I can use more efficient algorithms or data structures to improve performance? |
Debugging code can be a challenging and time-consuming process. However, with the help of ChatGPT, the process can be made much more manageable and efficient. By following the steps outlined in this article and keeping the tips in mind, you can use ChatGPT to debug your code with ease. Remember to provide specific information, use natural language, consider the context, and test your code to ensure that the error has been fixed.

In conclusion, ChatGPT is highly useful for debugging code if you use the appropriate prompts. Specifying the language, asking open-ended questions, requesting line edits, and providing sample inputs/outputs are effective strategies to debug code and build error-free programs. With practice, debugging with ChatGPT will become second nature.
I hope you’ve enjoyed reading this blog as much as I’ve enjoyed writing it Now, if you’re feeling inspired to practice and learn, don’t just sit there like a bump on a log! Get out there and start flexing those brain muscles! Learn a new language, try a new skill, or just learn a few new jokes to impress your friends.
And remember, sharing is caring! Don’t keep all that newfound knowledge to yourself, share it with your friends, family, and coworkers. Who knows, you might even inspire them to start learning too! And if not, at least you’ll have someone to tell your new jokes to.
So go forth and learn, my friends! And always remember, knowledge is power, but a good sense of humor is even more powerful.
Conclusion :
Hey there, fellow data enthusiasts! If you’re hooked on my articles and can’t get enough of my witty data humor, then you’re in luck! Here are three ways you can stay connected with me:
A. Follow me on LinkedIn and join my network of awesome data professionals. You’ll never miss a beat when it comes to my latest stories, tips, and tricks.
B. Subscribe to my newsletter, the ultimate insider’s guide to all things data engineering and data visualization. You’ll get exclusive access to new stories, and you can even text me to ask all the burning questions you’ve been dying to know.
C. Become a referred member, and get ready to indulge in an endless buffet of data knowledge. You’ll never have to worry about hitting your “maximum number of stories for the month” limit again, and you’ll get to read everything that I (and thousands of other top data writers) have to say about the newest technology available.
So what are you waiting for? Let’s get connected and start exploring the exciting world of data together! Oh, and don’t forget to bring the coffee — it’s the secret ingredient to unlocking the full potential of your data brainpower. Cheers!

So come on, let’s dive deep into the wonderful world of data together! Check out my website at vizartpandey.com, connect with me on LinkedIn at linkedin.com/in/rajvivan, or shoot me an email at rajeev.pandey11@gmail.com. Can’t wait to hear from you!