The “why” behind the quality assurance process that flows through the software development lifecycle will always be the same: Ensuring that software delivered to customers is fit-for-purpose, secure, and meets customer requirements.
However, the “how” has evolved. Testing has grown with technology, from creating and tracking test cases in spreadsheets and manually drafting testing documentation to leveraging test case templates and utilizing automated testing.
In other words, it’s natural for the software development community to be curious about the impact that ChatGPT will have on the trajectory of software testing.
Put simply, using the platform’s natural language processing and algorithms, QA professionals can use ChatGPT to:
So what do all these factors mean for software testers?
Ultimately, if QA professionals know the bounds of ChatGPT, it can be great for:
Here is the output from ChatGPT when prompted with "Create a test case for adding an accordion on a page":
Although not perfect, the output from ChatGPT is a great starting point, especially for front-end test cases. The output includes the main elements of a test case, provides specific steps, and is written in straightforward language.
Some of the more prominent limitations in using ChatGPT for software test case writing include:
To summarize, there is no denying the power of ChatGPT and its natural language model. Once you recognize the potential for AI to redefine many facets of your personal and professional life, there’s no looking back. However, the limitations of the technology will still require experienced QA professionals and developers to check its work, understand the subjective elements of design, utilize test management tools to manage the overall process, and deliver real-time, unique insights that only humans can provide. I don't think ChatGPT—and other AI-enabled platforms—will replace the need for sound development and QA, but rather be another tool in the toolbox professionals can use to amplify their impact.
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