How to Leverage ChatGPT for Code Debug?

Are you wondering how to use ChatGPT for code debug tasks?

ChatGPT is based on a large language model (LLM) by OpenAI that uses generative AI to understand human language and perform a variety of natural language processing tasks, including text generation, summarization, etc. 

As OpenAI models are available for everyone, you get an incredible opportunity to explore these advanced AI models and utilize them for creative purposes. 

If you are a software developer or a CTO leading a team of developers, you might be rightly interested in how ChatGPT can help write bug-free or debugging code written by you or your team.

While it is not possible to rely entirely on an AI model for building a fully functional software application, you can use ChatGPT to review your code, debug it, offer code suggestions, etc., in way less time.

Developing a custom application powered by an advanced AI model requires a deep understanding of deep learning, natural language processing techniques, chatbot technology, etc. 

If you don’t have a professional team with this relevant expertise to take on the task, then submit a request for a complimentary discovery call, and one of our tech account managers who managed similar projects will contact you shortly.

Let’s explore how you can utilize ChatGPT functionality for code debugging:

ChatGPT for Code Debug

The following points can help you use ChatGPT effectively to review your code for errors and suggest improvements:

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Identify the problem

The first step is to narrow down the problem in your code. This is essential as you must describe the problem you are facing in detail to ChatGPT for it to help you resolve the code issue. 

You should include error messages that you get on code build or run so that the AI model can better assist you.

Share code and give context

Include the code snippet that gives an error in the ChatGPT prompt. Provide as much information as possible related to the code function, input parameters, return values, etc.

You can also elaborate on used technologies, libraries, etc., for ChatGPT to understand the debugging problem effectively.

Ask for multiple suggestions

You can ask for alternative solutions during the coding process. By asking for several solutions, you get the opportunity to compare and choose the most relevant solution to your code problem. You also get to know multiple approaches and techniques to solve a particular issue.

Request troubleshooting steps

Ask ChatGPT to describe code troubleshooting steps and debug the issue. For example, you can ask “What are the steps to debug Swift code using Xcode IDE?” or “How can I place breakpoints in Python code using PyCharm IDE?”

Refine ChatGPT answers

Ask questions to clarify and understand ChatGPT explanations for possible code issues. ChatGPT is an AI model, and its suggestions might not be best for your distinct coding scenario. Make sure to verify ChatGPT information.

Iterate your code problem

If ChatGPT suggestions do not rectify your code problem, try redefining your issue. Refine your prompts and provide more specific information. Multiple interactions with ChatGPT increase the chance of getting the most accurate solution to your code problem.

Use a ChatGPT debugger package

Search for ChatGPT debugger libraries and packages that you can directly add to your project to locate and resolve code issues instantly in your IDE (integrated development environment). 

For example, the chatGPT-debugger package by PyPI allows you to debug Python code using ChatGPT3. It provides a detailed explanation of why the error occurs, shows how to fix it, and gives a corrected version of the code. 

Such utilities accelerate the process of code writing and debugging whether you are a beginner or an experienced programmer.

Example Prompts to Use ChatGPT for Code Debugging

Consider the example prompts to ask ChatGPT to debug a code snippet:

A. The following is a Python function to find all prime numbers within a given range. However, there seem to be some errors in the code, as it is not giving the correct output (prime numbers) as expected.

I need you to debug the code and provide the correct code that accurately finds the prime numbers within the given range.

Input:

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The input to the find_primes function is a range represented by start and end, within which the function should identify prime numbers. For this example, the start_range is assigned the value 10, and the end_range is assigned the value 30.

Output:

The correct output for the provided input should be a list of prime numbers between 10 and 30.

ChatGPT gives the following response:

Issues to Address:

The function is_prime is not accurately identifying prime numbers. It falsely identifies some non-prime numbers as prime.

The function find_primes does not consider the end value as part of the range to check for prime numbers.

Corrected code:

def is_prime(num):
    if num < 2:
        return False

    for i in range(2, int(num**0.5) + 1):
        if num % i == 0:
            return False
    return True

def find_primes(start, end):
    primes = []
    for num in range(start, end + 1):
        if is_prime(num):
            primes.append(num)
    return primes

start_range = 10
end_range = 30
result = find_primes(start_range, end_range)
print("Prime numbers between", start_range, "and", end_range, "are:", result)

B. Please provide the corrected version of the longestPalindromeSubstring function. It should correctly find the longest palindrome substring in the given input string. You can make necessary changes or use additional helper functions to achieve the correct output.

Input:

The input to the longestPalindromeSubstring function is a string for which we need to find the longest palindrome substring. In this example, inputString is assigned the value “babad”.

Output:

The function should find the longest palindrome substring in the input string and return it. The correct output for the provided input should be “bab” or “aba”.

ChatGPT gives the following response:

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Issues to Address:

The nested loops in the longestPalindromeSubstring function are not correctly considering all possible substrings.

The function does not handle cases where the longest palindrome substring has an even length (e.g., “abba”).

Corrected code:

function isPalindrome(s) {
    return s === s.split('').reverse().join('');
}

function longestPalindromeSubstring(input) {
    let longest = '';
    for (let i = 0; i < input.length; i++) {
        for (let j = i + 1; j <= input.length; j++) {
            let substring = input.slice(i, j);
            if (isPalindrome(substring) && substring.length > longest.length) {
                longest = substring;
            }
        }
    }
    return longest;
}

let inputString = "babad";
let result = longestPalindromeSubstring(inputString);
console.log("The longest palindrome substring is:", result);

Ready to Use ChatGPT for Code Debugging?

ChatGPT is an effective tool for debugging code, just like for many other NLP tasks. Though based on a generative AI model and trained on a huge data set, it can not replace human expertise in code debugging. 

We suggest you utilize AI tools like ChatGPT to augment your team’s code testing expertise and not consider it a definite solution to debug your code.

Working with an advanced AI model to undertake your custom NLP problems is a complex project that requires an exceptional understanding of deep neural networks, ML development tools and libraries, statistical techniques, large language models, etc. 

If you have such custom ChatGPT project requirements, DevTeam.Space can provide you with all the necessary expertise via a field-expert software developers community.

You can outsource your complete AI development project to our dev teams or hire individual vetted developers to augment your current development team. 

You can write to us your initial project specifications, and one of our tech account managers will get in touch with you shortly for further assistance.

FAQs on ChatGPT for Code Debug