In the rapidly evolving landscape of software development and quality assurance (QA) testing, artificial intelligence (AI) breakthroughs have been revolutionizing traditional approaches. Among these advancements, ChatGPT, a state-of-the-art language model developed by OpenAI, is poised to transform the QA testing landscape as we know it.
With its remarkable ability to understand and generate human-like text, ChatGPT is set to introduce a new era of efficiency, accuracy, and scalability in QA testing.
In this post, we will explore three example scenarios for how ChatGPT can reshape the field of QA testing, promising an exciting future for software development and quality assurance professionals.
Three ways to use ChatGPT for software QA testing
ChatGPT can dramatically improve testing by reducing the time for daunting and repetitive tasks such as creating test cases and identifying test data.
It can be a game-changer for software QA testers. Here are some ways ChatGPT can dramatically improve software testing efficiency:
- Test Case Generation: With ChatGPT’s language generation capabilities, QA testers can leverage the model to generate test cases based on predefined criteria automatically. By providing specific inputs and expected outputs, testers can prompt ChatGPT to create a set of test cases covering various scenarios and edge cases. This automation reduces the time and effort required for manual test case creation, enabling testers to focus on more critical aspects of testing.
We understand the daunting process of writing test cases, all our experts have first-hand experience, and that’s why we created a solution called QualityWatcher that uses AI to auto-generate test cases so testers can focus more on testing.
- Test Data Identification: ChatGPT’s natural language understanding and inference capabilities are ideal for identifying relevant and representative test data. Testers can interact with ChatGPT, describing the data requirements for their test scenarios. The model can then suggest suitable datasets or generate synthetic test data, saving substantial time and ensuring comprehensive test coverage.
- Test Automation Generation: ChatGPT can significantly reduce the time and effort required to write test automation for your application. ChatGPT knows what a typical Login, Register, or Add to Cart workflow looks like. Depending on the complexity of the application under test, ChatGPT may be more helpful in creating test automation. At QualityWorks, we have used our years of experience and knowledge of the domain to utilize AI and make it beneficial for typical workflows and complex applications.
Using ChatGPT’s capabilities in test case generation, test data identification, and test automation generation, software QA testers can significantly reduce the time spent on repetitive and labor-intensive tasks. This frees up their valuable time to focus on more complex testing activities, such as analyzing results, debugging, and improving overall test strategy. Ultimately, this leads to improved software quality, faster release cycles, and increased productivity for the QA testing team.
Three problems solved with example prompts
Writing test cases
ChatGPT can help with QA testing by reducing the time, effort, and expertise required to write test cases and test automation. Although writing test cases can be tedious and daunting, the creative use of ChatGPT to assist will drastically reduce the time spent writing test cases.
Use: Create test cases
Prompt: Write a simple test case with the title, steps, and expected result for adding a product to the cart.
Here is the prompt we used:
Creating test automation
The most time-consuming part of writing test automation is identifying element selectors. How can we use ChatGPT to identify the element selectors on a webpage?
Use: Create test automation
Prompt: Write a login test automation for Cypress.io to log in a user using email and password, following the page object model.
Here is an example of test automation code output from ChatGPT:
As a Quality Assurance tester, it can be tiring to identify test data, but this is something that ChatGPT can do for you.
Use: Create test data
Prompt: Give me 10 users for my application. Users should have a name, email, and password. Must be unique.
Here is the prompt for test data:
What are the benefits of using ChatGPT for software testing?
Tasks don’t take as much time as before.
With ChatGPT’s ability to automate repetitive and time-consuming activities, such as test case generation, test data identification, and even code snippet suggestions, QA testers can accomplish their tasks quickly and efficiently.
What once took hours or even days to complete can now be accomplished in a fraction of the time, allowing testers to focus on more critical aspects of testing, such as analysis, problem-solving, and enhancing overall test strategy. This time-saving advantage accelerates the testing process and enables faster feedback loops, shorter release cycles, and improved overall productivity for QA teams.
When testers bring their expertise together with the benefits of ChatGPT, they can reap significant benefits. The process requires that testers strategically use AI tools to get the correct output and their considerable testing knowledge to validate that output.
Testers have more time to focus on testing
By harnessing the power of ChatGPT in software testing, testers can reclaim valuable time previously consumed by manual and repetitive tasks. With ChatGPT speeding up the process of activities like test case generation, test data identification, and even code snippet suggestions, testers can redirect their efforts toward more critical aspects of testing.
This newfound time allows testers to focus on in-depth analysis, exploring complex scenarios, and refining test strategies, ultimately leading to higher-quality software and more efficient testing processes. As a result, ChatGPT becomes an invaluable ally, freeing up testers’ time and enabling them to deliver exceptional results.
Efficiency findings from QualityWorks’ ChatGPT experiment
Using ChatGPT to write test cases with the above prompts was up to 5x faster than manually creating test cases.
Depending on your expertise, manually writing a simple test case can take 5-10 minutes.
Using ChatGPT to write a test case took 1-3 minutes.
Using ChatGPT to write test automation was up to 2x faster than manually writing the test automation. The time savings in creating a test case multiplied by the several hundred test cases a project can require means you can have twice the test coverage with the same amount of time and effort. ChatGPT can easily give you page object files, test files, data files, configuration files, etc.
The test data files you get from ChatGPT give you a good starting point, will save you roughly half the time manually creating similar data, and allow you to do more with the time available.
Expertise and ChatGPT
Using ChatGPT can enhance and speed up the writing of test cases and test automation, but there is still a level of expertise required to get the desired outcome from ChatGPT.
Expertise is required to understand the desired output from each prompt, identify how to improve the results from the prompts and guide ChatGPT on what makes up a good test case or test automation. Also knowing how to use what was returned from ChatGPT effectively is now a skill that Quality Assurance experts must develop.
Like many use cases for ChatGPT, the output is a great starting point and can help with productivity. However, it still requires expertise to examine the output, determine its accuracy, and make expert adjustments.
The integration of ChatGPT in QA testing marks a significant turning point in the industry. Its benefits, such as faster task completion and enhanced automation, can transform how QA testing is conducted.
As QA teams embrace this transformative technology, they can elevate their testing processes, improve software quality, and drive business success. With ChatGPT leading the way, QA testing is poised for a future of unprecedented efficiency, effectiveness, and growth.