基于运行时监控的时间属性模糊框架

Jinjian Luo, Meixi Liu, Yunlai Luo, Zhenbang Chen, Yufeng Zhang
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引用次数: 0

摘要

现有的模糊器很难检测出时间属性所指定的缺陷。当程序执行包含一些特定的操作序列时,就会触发这些错误。这个扩展的抽象报告了我们最近在一个基于运行时监控的模糊框架上取得的进展,该框架针对的是表现为时间属性的bug。具体来说,我们提出了两种新的算法来保持输入突变体和改变输入种子,以提高模糊算法的效率。我们已经实现了Java程序的原型,并在真实的开源Java程序上进行了实验。初步的实验结果表明了该模糊方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Runtime Monitoring Based Fuzzing Framework for Temporal Properties
The detection of the bugs specified in temporal properties is difficult for the existing fuzzers. These bugs are triggered when the program executions contain some specific sequences of operations. This extended abstract reports our recent progress of a runtime monitoring-based fuzzing framework towards the bugs expressed as temporal properties. Specifically, we propose two novel algorithms for preserving input mutants and mutating the input seed to improve fuzzing's efficiency. We have implemented a prototype for Java programs and carried out experiments on real-world open-source Java programs. The preliminary experimental results indicate the promising of our fuzzing method.
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