Multi-Objective Optimization-Based Test Selection Algorithm Considering Test Reliability

Test selection represents a crucial step in testability modeling, ensuring diagnostic metrics while reducing testing costs. Nevertheless, in practice, the reliability of each test influences key indicators such as miss alarm rate and false alarm rate. Currently, most test selection methods rarely consider test reliability. This paper proposes a multi-objective optimization test selection method that accounts not only for the optimization of test costs, but also for the optimization of miss alarm rate and false alarm rate under the influence of test reliability. The effectiveness of the method is verified in several testing models.