Creating detailed test cases with AI

In the rapidly evolving world of software development and testing, AI is playing an increasingly significant role. Organizations aim for efficiency in the testing process, and leveraging AI alongside human expertise is the way to go. Read on to discover what it’s like to work with AI in software testing, with a focus on using AI for writing test cases.

Generating test cases with AI

A crucial step in software testing with AI is asking the right questions to obtain detailed test scenarios. It all starts with formulating a general question, which can then be used as a basis for follow-up questions. An example of such an initial question could be: “List me all test cases to test the following process in Finance, Microsoft Dynamics 365.” The list of test cases obtained from this may be too general but can serve as a foundation for further development. Therefore, it is essential to ask the right follow-up questions to AI. This is the only way to further refine test scenarios. For example, instructions on the length and detail of execution instructions make the scenario more specific. However, the cases are still not tailored to the business. Therefore, also ask for test data that the client can use if they want to run their own tests.

The indispensable human perspective on AI

It is important to realize that despite the assistance of AI, the end result is still the responsibility of the tester. It remains necessary to carefully review and validate the test case. AI systems can make mistakes or be limited by the data on which they are trained. The human perspective is essential to ensure that the test case is complete and relevant to the specific project.

The power of AI

The power of AI in generating test cases lies not only in speed but also in its ability to learn and adapt. By providing feedback on generated scenarios, the system can improve over time and produce more specific results. Through repetition of this process, the precision and importance of the generated test situations improve.

Data privacy

At Brightest, we utilize our own AI platform SQAI. Within this platform, a closed system with interface and database is set up for each client. This system is completely separated from other clients. Testers can create and refine test cases within this system, ensuring that confidential information remains within this interface. The use of such closed platforms not only provides convenience but also emphasizes the need to handle sensitive data responsibly. Customer privacy is thus not overlooked. If you choose not to use a closed system, it is advisable not to use sensitive information. Even when using examples, specific information should not be entered.

Conclusion

Integrating AI into the testing process offers significant benefits. However, it is important to remain aware of its limitations and the understanding that ‘real’ testers always carry the ultimate responsibility. We can conclude that asking the right questions, refining generated test cases, and using closed platforms ensure an advanced and secure environment in the rapidly evolving world of software development.