Focusing on the false positive problem of null pointer dereference (NPD) defect in static testing, a new false positive recognition method for null pointer reference defect based on classification was proposed. The knowledge of NPD defect was mined and preprocessed to generate data set of the defects. Then the data set of NPD defects was classified via ID3 classification algorithm based on rough set theory, and there were two kinds of classification results, one was false positive null pointer reference defect instances, the other was real null pointer reference defect instances. The real NPD defects were confirmed according to the classification results of the defect instances by recognizing the false positive NPD defects. The method was tested on ten benchmark programs and compared to the NPD defect detection method based on the mainstream static testing tool FindBugs, the false positive rate was reduced by 25%, and the confirmation amount was reduced by 24% for NPD defects. The experimental result shows that the proposed method can effectively reduce defect confirmation overhead and improve the detection efficiency and stability for NPD defects in static testing.