AI in API Testing: How to Test Faster With ChatGPT

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Start using AI at full power. Generate scenarios, write tests, and create test data faster with ChatGPT. The demonstration will be provided via Cypress tool.

Olga Trofimova
Olga Trofimova
26 min
07 Dec, 2023

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Video Summary and Transcription

This Talk discusses the use of AI in API testing and provides a step-by-step strategy for incorporating artificial intelligence with chat.dpt. It emphasizes the importance of analyzing documentation and creating test cases using tools like Swagger and Cypress. The Talk also addresses the role of human involvement in testing, the balance between manual work and AI assistance, and the need for validation of AI-generated tests. Overall, AI can significantly speed up the testing process, but human analysis and vigilance are still necessary for accurate results.

1. Introduction to AI and API Testing

Short description:

Hi, everyone! Today, I'll share a step-by-step strategy for API testing and discuss how incorporating artificial intelligence with chat.dpt can elevate your testing process. Let's dive into the heart of the matter. API is an important layer in the application, and the chat can help us delegate monotonous work to AI. I joined Spleeky as the only QA and had to start everything from scratch. The chat was a popular tool, so I decided to experiment and give it a try. Let's focus on versions 3.5 and 4.2.0, as they have their pros and cons.

Hi, everyone, and thank you for joining me today. My name is Olga, and I am honored to be your guide in the intersection between artificial intelligence and API testing. So I believe that you will learn new tips and approach today.

Today, I'll share with you a strategy for API testing, step by step, and discuss why incorporating artificial intelligence, particularly with chat.dpt, can elevate your testing process to a new level. So in today's examples, we will learn and we will see how to use the chat for REST API and GraphQL.

But first, a bit about myself. My current position is QA manager at Spleeky. For most of my life, I worked with automation, built processes from scratch, and tried different test frameworks. Also, I'm a huge fan of life improvement. I love mountain climbing and so on. For example, last month I climbed on a height of 3,000 meters and the Alps. But at work, I love to ease, but not to complicate. So now let's dive into the heart of the matter.

API is one of the important layers in the application. It's very easy to understand why. It's important to cover. If we have a look at my conspire pyramids, here API tests are set at the integration level, which is supposed to be the second batch of our tests. So how can the chat help us at this stage? The main point is we can delegate monotonous and repetitive work to AI. Let me illustrate how things used to look in my company. I joined Spleeky this summer, and I was the only QA at the project. The team tested features on their own, but there were no QA or QC processes or test documentation, so I had to start everything from scratch. We had unit tests, but we also needed end-to-end tests and covered endpoints with API tests. At the time, we had 30 endpoints in REST and 20 in GraphQL. When you start from scratch, you are usually pressed for time. And I was looking for a popular and convenient tool for boosting my work. The chat was on everyone's lips, so I just decided to experiment and give it a try to find out whether it was worth it or not. And the chat has two versions, 3.5 and 4, but they also released version 4.2.0, but let's focus today just on the first two. Of course, all these have their pros and cons. Version 3.5 is free, but it takes just text. News makes mistakes.

2. Testing Strategy and Documentation Analysis

Short description:

The last update was in January 2022, and version 4.0 requires payment for premium features. However, it supports various file formats and can generate images. The testing strategy involves checking specifications and performing various steps, such as verifying status codes, payload, headers, and basic performance. Practice begins with analyzing the documentation using specific steps.

And the last update was in January 2022, which means that it doesn't have access to the newest information. And as for version 4.0, to unlock the premium features, you need to pay for it. That's the bad news.

But it takes not only text, but other files formats such as PDFs, tables, images, audio, videos, and archives. What's more, it can generate images itself. And as for the knowledge update, the last time was in April 2023. That means that this version is more relevant.

Now I'm going to go into the testing strategy. The testing strategy consists of two steps. First and foremost, we need to check specifications. We always need to start from this step. This is also important to be sure that endpoints are named correctly, that resources and their types depict the correct model, and there is no lack of duplicated functionality.

Then comes to testing itself. As for the testing, it can be broken down into several steps. Firstly, it's necessary to check the actuality of the status code. When you send, for example, a post request and create new item, you should get 201 status code. If we send a request which is forbidden, we expect 403 status code. Then check the payload. Check that the body JSON names, types, and fields are correct. Don't forget about requests with an error response. The third thing you need is check the headers of response. Headers are critical because they affect security and performance. The last step you need to do is check basic performance. In case the operation was a success but took a lot of time, the test is still considered failed.

Now, it's time for practice. Before I start, please keep in mind that it's not safe to share sensitive data. Always clear it. Let's start with the first stage, documentation. So create a prompt and ask the chat to analyse the documentation. For this purpose, we can use several steps.

QnA

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