In recent years, artificial intelligence has played an increasingly important role in software development.
One of the latest advances in this area is ChatGPT, a natural language processing neural network that can be trained to perform various tasks, from text generation to natural language understanding.
ChatGPT can also be used to help automate many common tasks when it comes to software development, making it faster, more efficient, and more accurate.
Want to know more? Read on to find out 6 practical applications of ChatGPT in software development and how this technology may be used to improve quality and speed for devs.
But first, let us understand the concept behind this technology.
What is ChatGPT?
ChatGPT is a natural language model created by OpenAI, an artificial intelligence research company. It was trained using a machine learning technique called “transformer”, which allows the model to learn how to predict the next word in a sentence based on the previous context.
The software is a version of the GPT (Generative Pretrained Transformer) model that has been pre-trained on a large amount of internet text data. This prior training allows the model to generate new, coherent text in response to a question or statement given to it.
In practice, the model is able to understand a wide variety of topics and can answer questions on almost any subject in which it has been trained. It is designed to be able to hold a natural-like conversation flow with users, using a fluid and spontaneous language.
Now that you understand what ChatGPT is, let’s see how it can be used to help in the development of systems.
6 practical applications of ChatGPT in systems development
Although it has already been used in a variety of applications, from voice assistants on smart home devices to customer service chatbots in various enterprises, ChatGPT is also often used as a research tool for development in artificial intelligence and natural language processing.
But, speaking of the world of devs, here are the 6 main uses of ChatGPT technology in this sense:
1. Task Automation
ChatGPT can be used to automate tasks that involve natural language processing, such as auto-filling forms, generating personalized emails, and more.
Although these situations involve less code, they are part of the dev day to day routine and may contribute towards increasing the productivity of the team in general.
2. Code debugging and analysis
Another important use of ChatGPT is in the programming process, where the model can provide code suggestions and/or correct errors, and still provide context about an eventual functionality of the algorithm and the expected result.
It can also explain in natural language how the code works, which can help developers understand it more deeply in order to identify bugs and raise the overall quality of the work.
3. Evolve test quality
Another practical application of ChatGPT is in software testing, which is an essential step in the development process.
In order to do this, it is necessary to create a robust test automation with high coverage to catch failures and prevent problems from reaching the publication of the system. In this sense, ChatGPT can help create test cases to identify bugs that are not so obvious to the dev.
4. Identification of extreme use and failure cases
Because it has a lot of computational power, ChatGPT may be able to generate extreme situations where code will fail—and that you may not be able to identify through most of the common tests generally used to test this.
Although these situations are usually expected, it is important to solve them to improve the quality of the product and maintain user satisfaction.
5. Code Generation
One more cool application of ChatGPT is in its use in order to generate completely new code based on a high-level description of what that code should do.
For example, if a developer needs to create a program that sorts a list of names alphabetically, they can describe that goal in natural language to ChatGPT, which can then generate the code needed in order to accomplish that task.
Pretty cool, right?
In addition, you can provide code examples for common tasks, such as reading a text file or formatting input data. This helps save developers time as they do not have to spend a lot of energy on trial and error processes as they used to.
6. Creation of system documentation
The last practical application of ChatGPT in software development is in the creation of software documentation, since the tool can create natural language explanations for the written code.
For example, developers can provide a description of the code and how it works, and the model can generate more detailed documentation explaining the logic behind the code.
You can also work with API documentation, describing how to use and interact with the software. Here, developers can provide information about API methods and parameters to ChatGPT, which can then generate clear and concise documentation about their use.
As we can see, the use of Artificial Intelligence has grown a lot, far beyond recommendation systems and personal assistants such as Alexa and Siri in recent years.
And although they are extremely competent, it is important to note that the human eye is still very much necessary in order to properly assess whether the results of the interactions with the AI make sense. In this way, we can extract a lot of power—going beyond what we have seen here—to create robust, flawless, and useful software for users.
Did you enjoy getting to know a little more about the practical applications of ChatGPT in the development of systems? So, please also take the opportunity to read: How to develop quality software: 4 principles to improve a product
