基于静态检测工具的软件缺陷检测模型研究

摘要

针对如何降低静态检测工具的误报率、漏报率和重报率这些问题,本文研究设计一个基于静态检测工具的软件缺陷检测模型.该模型通过对不同的静态检测工具的检测结果进行多级处理,有效地降低误报率、漏报率和重报率.最后,将两种静态检测工具应用于该模型,对开源软件NMap进行缺陷检测,实验结果表明该模型的有效性和实用性.%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.