FEData
收藏资源简介：
FEData是一个专为模糊测试评估设计的数据集，由斯文本科技大学创建。该数据集包含18000个C程序，这些程序是从GitHub下载并经过处理的，以包含特定的搜索阻碍特征，如数据流触发错误、执行路径数量、魔法值数量和校验和数量。FEData的目的是通过这些特征来评估模糊测试工具的性能，并帮助改进这些工具。数据集的应用领域主要集中在软件安全工程，特别是模糊测试的效率和效果评估。
FEData is a dataset specifically developed for fuzz testing evaluation, created by Swinburne University of Technology. This dataset comprises 18,000 C programs downloaded from GitHub and processed to incorporate specific search-impeding features, including data flow-triggered bugs, the count of execution paths, the number of magic values, and the quantity of checksums. The core objective of FEData is to evaluate the performance of fuzz testing tools based on these features and facilitate the improvement of such tools. The primary application scope of this dataset lies in software security engineering, specifically for the efficiency and effectiveness evaluation of fuzz testing.
