Can Generative AI Produce Test Cases? An Experience from the Automotive Domain
Stephen Wynn-Williams, Ryan Tyrrell, Vera Pantelic, Mark Lawford, Claudio Menghi, Phaneendra Nalla, Hassan Ali Artail · 2025
Engineers need automated support for software testing. Generative AI is a novel technology for generating new content; however, its applicability for test case generation is still unclear. This work considers the following question: Can generative AI produce test cases in industrial software applications? We framed our question in the automotive domain. We performed our evaluation in collaboration with a large automotive manufacturer to assess to what extent generative AI can produce test cases (a.k.a. test scripts) from informal test case specifications. We considered 1) informal test case specifications defined in Rational Quality Manager, an industrial test management tool from IBM, and 2) executable test scripts specified as ecu.test packages supported by the ecu.test tool from Tracetronic. We used generative AI to produce the test scripts from the informal test case descriptions. Our results show that generative AI can produce correct or near-correct test scripts in a reasonable number of cases. We also analyzed the effects of prompt design, choice of generative AI model, and context accuracy on the effectiveness of our solution and reflected on our results.