Top 3 Use Cases & Tools

Generative AI is one of the latest tech trends that has already started to be used in various industries such as:

However, it also has a powerful influence on the software development process with various tools developed for writing and optimizing codes. In this article, we will explain the top 3 use cases of generative AI coding application and address 3 AI coding tools. 

Code generation 

Writing code with generative AI is possible through a technique known as neural code generation. This involves training a neural network on a large dataset of code examples, and then using the fine tuned network to generate code that is similar in structure and function to the examples it has been trained on.

Figure 1. Generating an HTML form and JavaScript submit code with OpenAI’s ChatGPT

Source: Medium¹

Code completion 

One of the most straightforward uses of generative AI for coding is to suggest code completions as developers type. This can save time and reduce errors, especially for repetitive or tedious tasks.

Code review 

Generative artificial intelligence can also be used to make the quality checks of the existing code and optimize it either by suggesting improvements or by generating alternative implementations that are more efficient or easier to read.

Figure 2. The mechanism of Amazon’s CodeWhisperer for reviewing code

Source: Amazon

Besides these top 3 coding use cases, there are other applications of generative AI for software engineering tasks such as:

• Bug fixing: It can help identify and fix bugs in the generated code by analyzing code patterns, identifying potential problems, and suggesting fixes.
• Code refactoring: It can be used to automate the process of refactoring code, making it easier to maintain and update over time.
• Style checking: It can analyze code for adherence to coding style guidelines, ensuring consistency and readability across a codebase.

1- GitHub Copilot

GitHub Copilot, Microsoft’s AI system to write code, is an AI-powered code suggestion and generation tool developed in collaboration with OpenAI. It uses machine learning models trained on a vast corpus of public code to suggest code snippets and even entire functions as developers type.

 Figure 3. Survey responses measuring dimensions of developer productivity when using GitHub Copilot

Source: GitHub Blog

According to executives at GitHub and other companies, the aim of these tools is not to substitute developers, but to enhance their efficiency, similar to the way spell check and phrase auto-completion tools help people in writing documents.² 

The results of it can be seen in the survey done with developers (see Figure 3). These tools suggest fresh code snippets and tests, and give technical advice within the existing code-writing programs that developers use.

2- ChatGPT

As an AI model developed by OpenAI, ChatGPT does not have a specific code generation function. However, as a language model trained on a large corpus of text data, it can generate text in natural language, which includes code snippets or examples, when prompted to do so.

For example, if a user asks “Can you provide an example of a Python function that calculates the sum of two numbers?” ChatGPT can generate a code snippet in response, such as in Figure 4.

Figure 4. An example of ChatGPT generating code for the given prompt and explaining it

While ChatGPT is not specifically designed for generating code, it can be trained on a dataset of code examples to improve its ability to generate code snippets and functions that are syntactically correct and functionally valid. However, it’s important to note that the quality of the generated code may vary depending on the quality and quantity of the training data and the complexity of the task being performed.

ChatGPT could be a good debugging companion; it not only explains the bug but fixes it and explain the fix 🤯 pic.twitter.com/5x9n66pVqj

— Amjad Masad ⠕ (@amasad) November 30, 2022

3- CodeWhisperer

Amazon’s CodeWhisperer is a code generation tool that utilizes diverse data sources, including Amazon.com and open-source code, to produce code that imitates the way a developer would write it. 

It comprehends comments expressed in natural language, creates code based on the developer’s objectives, and corresponds to the developer’s style and patterns. Additionally, while typing, CodeWhisperer offers suggestions to complete the comment. Users have the option to accept the top suggestion, view additional recommendations, or proceed with writing their own code.

For other code generator tools and information about their features and pricing, you can check our generative AI tools article.

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1. “ChatGPT AI — Better than a developer? | by Edouard Courty.” Medium, 6 December 2022, https://medium.com/@edouard.courty/chatgpt-ai-better-than-a-developer-b1858522e6b4. Accessed 5 March 2023.
2. “Generative AI Helping Boost Productivity of Some Software Developers.” The Wall Street Journal, 21 February 2023, https://www.wsj.com/articles/generative-ai-helping-boost-productivity-of-some-software-developers-731fa5a. Accessed 5 March 2023.