摘要:针对当前Windows下GUI软件模糊测试过程中，由于进入空转状态时刻判断不准确导致的测试效率降低的问题，利用自然语言处理的方法在函数执行迹的基础上来解决空转状态识别问题.首先分析了传统程序分析方法在空转状态判断上遇到的困难，提出了基于Bi-Gram模型以及统计分析的空转状态识别方法.通过Bi-Gram算法，将程序函数执行迹转换为概率特征序列；利用空转状态在特征序列中的方差特征，将空转状态特征序列从程序特征序列中分离，在此基础上，进一步提取空转状态特征并实现空转状态实时检测算法.通过对典型源码与二进制软件程序的实验测试表明，该方法在效率和准确性上优于传统方法，能够支撑对GUI程序模糊测试的需求.



Abstract:GUI program's idle state usually causes low efficiency of fuzzing test.This paper tries to solve idle state detecting problem based on function trace by nature language processing method.It first analyzes the difficulties that traditional program analysis method faces in idle state detection,and then proposes an idle state detecting method based on Bi-Gram module and statistical analysis.Bi-Gram algorithm transforms the function trace of the GUI program to probabilistic characteristics sequence,then segregates the idle state probabilistic characteristics sequence from prgram's probabilistic characteristics by variance characteristics in idle state probabilistic characteristics sequence.The algoritnm finally extracts idle state features which applied to the real-time idle state detecting algorithm.Experiments of source code and binary program show that the new method is more efficient and accurate than traditional method.



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