通过程序生成和差分测试自动测试符号执行引擎

Timotej Kapus, Cristian Cadar
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引用次数: 50

摘要

近年来,符号执行在软件测试、安全、网络等方面的应用引起了人们的极大关注。符号执行工具,如CREST、KLEE、FuzzBALL和Symbolic PathFinder,使研究人员和实践者能够试验新的想法,将技术扩展到更大的应用程序,并将其应用到新的应用领域。因此,这些工具的正确性至关重要。在本文中,我们介绍了扩展编译器测试技术以发现符号执行引擎的具体执行组件和符号执行组件中的错误的经验。所使用的方法依赖于一种新的方式来创建程序版本,在三种不同的测试模式下——具体的、单路径的和多路径的——每一种都使用符号执行引擎的不同功能。当与现有的程序生成技术和适当的oracle相结合时,这种方法可以在单个符号执行引擎中进行差异测试。我们已经将我们的方法应用于KLEE, CREST和FuzzBALL符号执行引擎,在那里它已经发现了20个不同的错误,暴露了与处理结构,除法,模,转换,矢量指令等有关的各种重要错误,以及与约束解决,编译器优化和测试输入重放相关的问题。
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Automatic testing of symbolic execution engines via program generation and differential testing
Symbolic execution has attracted significant attention in recent years, with applications in software testing, security, networking and more. Symbolic execution tools, like CREST, KLEE, FuzzBALL, and Symbolic PathFinder, have enabled researchers and practitioners to experiment with new ideas, scale the technique to larger applications and apply it to new application domains. Therefore, the correctness of these tools is of critical importance. In this paper, we present our experience extending compiler testing techniques to find errors in both the concrete and symbolic execution components of symbolic execution engines. The approach used relies on a novel way to create program versions, in three different testing modes—concrete, single-path and multi-path—each exercising different features of symbolic execution engines. When combined with existing program generation techniques and appropriate oracles, this approach enables differential testing within a single symbolic execution engine. We have applied our approach to the KLEE, CREST and FuzzBALL symbolic execution engines, where it has discovered 20 different bugs exposing a variety of important errors having to do with the handling of structures, division, modulo, casting, vector instructions and more, as well as issues related to constraint solving, compiler optimisations and test input replay.
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