Abstract: To cope with the problems about how to reduce the false positives, false negatives and repeated rate, this paper presents a software defect detection model based on static testing tools. This model processes the test results of different static detection tools, and analyzes the final merged result, which effectively reduces the false positives, false negatives and repeated rate. Finally, by using two static detection tools, this model detects an open-source software named “NMap”. The experimental result shows the effectiveness and practicality of this model.

Key words: software defects, static detection tools, repeated rate, false positives, false negatives