Software fault localization is a time-consuming and laborious work, so determining how to improve the automation of software fault localization has always been a hot topic in the field of software engineering. The existing spectrum-based fault localization (SBFL) methods rarely use the context information of the program, which is very important for fault localization. To solve this problem, this study proposes a fault localization approach based on path analysis and information entropy (FLPI). Based on the spectrum information technology, this approach introduces the execution context information by analyzing the data dependencies in all execution paths, and introduces the test event information into the suspiciousness formula by using the information entropy theory, so as to maximize the accuracy and efficiency of fault localization. To evaluate the effectiveness of the proposed approach, the experiments are conducted on a set of benchmark programs and open source programs. Experimental results show that the proposed FLPI approach can effectively improve the accuracy and efficiency of fault localization.