Requirements Dependency Driven Test Case Generation: An Automotive Industry Practice

Tong Xu, Zheng Zhou, Xiaohong Chen, Zhiyi Xue, Yi Zhao, Min Zhang, Zhi Jin

Abstract: In the automotive industry, automated hardware-software integration testing is of vital importance for ensuring software quality and reducing project costs. However, in practice, the generation of automated test cases for such testing faces many challenges, primarily due to the complexity, implicit, and difficulty in identifying requirement dependencies. To address this issue, this paper proposes a requirement dependency-driven automated test case generation method. This method utilizes large language models to directly extract structured models, e.g., flowcharts, from natural language requirements documents. By analyzing these flowcharts, it can accurately identify implicit requirements dependencies and generate test scenarios, thereby specifying the execution order and temporal constraints for test case generation. In a real-world case study with the Beijing Automotive Industry Corporation (BAIC), the method successfully processed 300 functional requirements and identified a total of 4731 implicit dependencies. The content accuracy rate of the generated flowcharts reached 81.24%, and the business scenario coverage rate of the test cases reached 82.67%. These results preliminarily demonstrate the effectiveness and feasibility of our approach, significantly enhancing the level of automation in automotive integrated testing and providing strong technical support and reference for related practices in the industry.

External IDs:dblp:conf/re/XuZCXZZJ25