What is ChatGPT stands for? (Chat Generative Pre-trained Transformer)

ChatGPT is OpenAI's artificial intelligence that answers complex questions. It is an exciting new technology that is being trained to understand and answer questions asked by people IRL.

His human-like response ability shocked the world, sparking the idea that he could one day change the way people interact with computers and search for information.

In November 2022, OpenAI launched ChatGPT, a chatbot with a large language model. As a result, you can communicate with the chatbot in a variety of ways. The language model can help you with coding, creating an email, writing an essay, and answering your questions. Both reinforcement learning and supervised learning approaches are used to fine-tune ChatGPT.

ChatGPT was trained by collecting a significant amount of data with a cutoff date of October 2021. Then, using additional human-tagged datasets, the model was continuously evaluated and refined for various language-oriented tasks. It is fascinating to see how it can engage in conversation and respond with comments that sometimes seem quite insightful.

From a technical point of view, ChatGPT is categorized as generative AI. Once trained, a generative AI model can generate results similar to the training data, but not exactly the same.

How ChatGPT benefits developers

1) Code generation

In terms of code generation, ChatGPT is a powerful tool for developers. ChatGPT can understand and interpret the developer's needs using its natural language processing skills and provide relevant code snippets. When it comes to repetitive tasks or template code, it can save programmers a lot of time.

Instead of creating basic functionality, ChatGPT can create complex code for tasks such as building an entire class or module. This allows developers who are not familiar with a programming language or framework to quickly learn them without spending a lot of time learning the basics, which can be very valuable for novice programmers.

In general, ChatGPT's code generation capabilities can be useful for developers of any level, as it helps to focus on the most important aspects of the project. At the same time, the model takes care of repetitive and time-consuming tasks. In addition, it reduces the probability of errors and inconsistencies and saves time.

Here are the results of ChatGPT when I asked it to create a React component with the given requirements. I specifically asked to use the "React Beautiful DND" library, and ChatGPT created a fully functional React component that met all my requirements. This was an outstanding result. ChatGPT included all the features I requested and the application worked as expected. The key point is its comprehension; it met all my needs perfectly.

2) Document generation

Thanks to its natural language processing capabilities, ChatGPT can accurately generate documents that identify requirements. Developers who often have to spend a lot of time developing comprehensive documentation for their code can benefit significantly from this in terms of time savings.

For example, a developer can give ChatGPT a piece of code and have it create documentation explaining the function's purpose, inputs, outputs, and other important details. Alternatively, ChatGPT can create documentation for entire classes or modules, providing a comprehensive overview of the code.

In addition, ChatGPT can provide documentation in various forms such as Markdown, HTML or JSDoc, allowing developers to easily integrate it with their code editor.

For developers of any skill level, ChatGPT's ability to create code documentation will be very useful, as it frees them from their work and allows them to focus on more important elements of the project. At the same time, the model completes the time-consuming process of code description. Thus, by using ChatGPT, developers can be sure that their codebase is well documented, making it easier for other developers to understand and work with.

Below is the result of ChatGPT when asked to generate documentation for a given code snippet. This is a simple wrapper function that wraps the Axios 'get' method.

In the documentation created by ChatGPT, you can see that the purpose of the function and the use of all parameters are precisely defined. In addition, ChatGPT has provided sample code to identify the function in more detail. This is very useful for documentation and ChtGPT has done a great job here.

3) Writing test cases

ChatGPT can assist developers in writing test cases in a number of ways. One of them is to define the purpose of the test case, create the input data and the expected test results. For example, if a developer asks ChatGPT to write a test case that can handle invalid input. In this case, ChatGPT may generate invalid input such as special characters, empty strings, and out-of-range values.

ChatGPT is useful when writing test cases because of its ability to determine the logic and structure of the code you provide. Because of this, ChatGPT can write test cases that cover different code paths and edge cases. For example, if a developer provides a piece of code and tells ChatGPT that this code should be able to handle large data sets. In this case, it can create test inputs with large data sets.

ChatGPT can also be used to generate test case documentation. It can generate concise and clear descriptions of test cases, including test inputs, predicted results, and conditions under which the test should pass or fail. As a result, developers, even those with no testing knowledge, can quickly update specified test cases.

Below is the result I received in ChatGPT after requesting to generate a test case for the "getHttpMethod" wrapper function mentioned above.

If we parse the ChatGPT result, we can see that ChatGPT used Jest and that the generated test case includes two tests. The response of the GET request is compared to the expected result and it is checked if the function works as expected.