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Top 7 ChatGPT Coding Use Cases in 2024

Cem Dilmegani
Updated on Jan 11
4 min read

ChatGPT is currently one of the most popular ones among generative AI tools. As a large language model, besides its text generation capability which is its most commonly used application area, it has other merits such as

  • Translation
  • SEO optimization
  • Search
  • Certain coding applications for software development

According to a research conducted by BlackBerry Global Research, 49% of IT decision-makers believe that ChatGPT will help hackers improve their coding skills.1 Whether this negative expectation will happen in the future or not, it is a fact that ChatGPT is a useful tool for coding applications. 

In this article, we provide 7 ChatGPT coding use cases with examples from this tool.

1- Writing code

ChatGPT can generate code for simple or repetitive tasks, such as file I/O operations, data manipulation, and database queries. However, it’s important to note that its ability to write code is limited and the generated code may not always be the accurate, optimized or desired output.

Figure 1. ChatGPT writing code for the comment “Can you write a Python program that reads a CSV file containing student data, calculates the average grade for each student, and writes the results to a new CSV file?”

ChatGPT is primarily designed to generate natural language text.Besides, instead of being specifically designed for writing code, it has been trained on large amounts of programming code. However, it can generate simple code snippets based on natural language inputs and can suggest improvements to the existing code.

It’s also worth noting that while ChatGPT can generate code, it cannot understand the underlying problem or requirements that the code is intended to solve. Therefore, the code generated by it may not always be the best or most efficient solution to the problem.

2- Debugging

ChatGPT’s bug fixing performance is also quite useful for programmers. It can debug code by suggesting potential causes of errors and providing solutions to fix them (See Figure 2). When a programmer encounters an error in their code, they can input the error message or code snippet into ChatGPT, and it can analyze the code and suggest possible solutions to fix the error.

Figure 2. ChatGPT helping with debugging code

3- Code completion

ChatGPT can help in completing the code by predicting the next lines or sections of code based on the context and existing code. This can save time and effort for programmers who may not remember all the syntax and functions of the programming language they are using. Code completion can also reduce errors by suggesting the correct syntax and formatting.

4- Code refactoring

ChatGPT can suggest ways to optimize and improve the code structure, readability, and performance. Refactoring involves modifying existing code to improve its quality without changing its behavior. ChatGPT can provide suggestions for changing variable names, removing redundant code, and other improvements that can make the code more efficient and easier to understand by other programmers.

Figure 3. ChatGPT refactoring a code it provides as an example

5- Code documentation

When a programmer inputs their code into ChatGPT, it can suggest appropriate documentation templates based on the programming language and the type of code being documented. For example, if the code is a function, ChatGPT can suggest a function documentation template that includes parameters, return values, and a description of the function’s purpose.

ChatGPT can also provide examples of best practices for documenting code, such as using descriptive variable and function names, including comments to explain complex code, and following established documentation standards for the programming language being used.

Figure 4. ChatGPT providing an example code documentation for a Python function that sorts a list of numbers in ascending order

6- Generating code snippets

ChatGPT is capable of generating code snippets in various programming languages based on user input and requirements. A code snippet is a small piece of code that demonstrates a specific feature, function, or technique in a programming language. Code snippets are useful for illustrating how to perform a specific task or solve a problem in code and can be used as a starting point for more complex programming projects.

When a user inputs a request for a code snippet, ChatGPT uses its natural language processing (NLP) capabilities to analyze the user’s input and generate a code snippet that meets the specified requirements. The generated code snippet may include various programming constructs, such as variables, loops, conditionals, and functions, depending on the specific task or problem being addressed.

Figure 5. ChatGPT provides an example code snippet

7- Explaining coding techniques & concepts

ChatGPT can provide explanations and examples of programming concepts, syntax, and functions, which can help learn and understand programming languages. This can be particularly useful for beginner programmers who may be unfamiliar with programming concepts or experienced programmers who are working with a new programming language.

Figure 6. ChatGPT explains the question “What is object-oriented programming and how does it work?”

Also, it can provide step-by-step instructions for solving programming problems and improving coding skills.

However, it is important to not rely solely on ChatGPT’s ability to provide explanations as it occasionally provides wrong answers according to user reports. Although it is a useful tool for learning quickly and easily, it requires double checking for the information it provides. You can learn more about this and other limitations through our in-depth guide on ChatGPT use cases and limitations.

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Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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