Abstract: Existing approaches to test case selection usually focus on how to improve the efficiency of testing, rather than the effectiveness of fault localization. To solve this problem, a test case selection approach is proposed. Firstly, “test case prioritization criterion by similarity of failure coverage vector” is proposed to prioritize the passed test case whose execution path is more similar to that of the failed test case. Secondly, “test case selection criterion by equivalent failure coverage division” is defined to select passed test cases, which can maximally differentiate the statements in the failure execution path. Finally, the test case selection model ES is created based on these two criteria. Different from existing approaches, ES takes advantage of the execution path of the failed test case to improve the effectiveness of fault localization. It has been applied to analyze the Siemens benchmark, and the selected test cases have been used as input of four popular coverage-based fault localization techniques. Experimental results show that in terms of the Reduction and Expense_increase metrics, ES is better than the existing statement-based and vector-based test case reduction approaches. ES can get a Reduction of over 97%, which indicates that it can greatly improve the efficiency of fault localization. In particular, ES can also achieve a low Expense_increase, which means it can significantly improve the effectiveness of fault localization.