In order to ease the time-to-market pressure of flash memory, we propose a fault-pattern based diagnosis methodology that reduces the burden in yield learning. The fault-pattern based diagnosis approach is based on defect dictionary and ATE log file. The proposed diagnosis method allows product engineers to quickly isolate defect candidates. In this paper we use open/short defects to demonstrate our method. We propose a diagnostic test algorithm for flash memory based on the targeted defect models. The length of the new diagnostic test is shorter than previous ones, so diagnosis time can be reduced. Experimental results show that the diagnostic resolution of fault-pattern based method reaches 83.3% for a NOR-type flash, and 100% for a NAND-type flash. We also present a current test to improve the diagnostic resolution for NORtype flash, so its diagnostic resolution can reach 100% as well.