Test case prioritization techniques have been empirically proved to be effective in improving the rate of fault detection in regression testing. However, most of previous techniques assume that all the faults have equal severity, which dose not meet the practice. In addition, because most of the existing techniques rely on the information gained from previous execution of test cases or source code changes, few of them can be directly applied to non-regression testing. In this paper, aiming to improve the rate of severe faults detection for both regression testing and non-regression testing, we propose a novel test case prioritization approach based on the analysis of program structure. The key idea of our approach is the evaluation of testing-importance for each module (e.g., method) covered by test cases. As a proof of concept, we implement $Apros$, a test case prioritization tool, and perform an empirical study on two real, non-trivial Java programs. The experimental result represents that our approach could be a promising solution to improve the rate of severe faults detection.