Proposing an Information Management Framework for Efficient Testing Strategies of Automotive Integration

The increasing quantity and complexity of code in vehicles have imposed a heavy burden on traditional integration testing methods. However, applying new testing methods, such as eliminating redundant test cases, prioritizing based on risk, and optimizing test matching, requires the testing team to possess sufficient information, which entails communication and time costs. In this study, an information management framework is developed for the integration testing phase of automotive software to assess the importance and acquisition difficulty of specific information. The framework mainly includes three core parts: (1) classifying 37 types of test-related information into five hierarchical levels (requirement level, architecture level, function level, component level, and source code level) based on risk theory; (2) designing a scale to evaluate the difficulty of information usage from three dimensions (acquisition, transmission, and evaluation); (3) providing an operational guide for integration testing departments to match information with testing strategies. This framework assists enterprises in making wiser decisions regarding testing methods and provides guidance for future collaboration between original equipment manufacturers and suppliers.