Execution reconstruction: harnessing failure reoccurrences for failure reproduction

Execution reconstruction: harnessing failure reoccurrences for failure reproduction
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执行重建:利用故障重复发生来重现故障

DOI:
10.1145/3453483.3454101
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发表时间:
2021
期刊:
ACM SIGPLAN Conference on Programming Language Design and Implementation
影响因子:
--
通讯作者:
Kasikci, Baris
Kasikci, Baris
中科院分区:
--
文献类型:
--
作者:
Zuo, Gefei;Ma, Jiacheng;Quinn, Andrew;Bhatotia, Pramod;Fonseca, Pedro;Kasikci, Baris

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重现生产故障对软件可靠性至关重要。唉,现有的错误复制方法不适合生产系统,因为它们不是同时有效、有效和准确的。在这项工作中,我们调查了现有的技术,并表明现有的方法优先考虑这些属性的子集,而牺牲了其余的属性。因此,现有的工具不能支持过多的针对生产故障的故障再现用例(如调试、安全取证、模糊)。我们提出了执行重构(ER),它在再现生产故障的效率、有效性和准确性之间取得了更好的平衡。ER使用硬件辅助控制和数据跟踪来引导符号执行和复制故障。ER的主要新奇之处在于确定了既易于监视又对摆脱符号执行的可伸缩性限制有用的数据值。ER通过迭代地执行跟踪和符号执行来利用故障重现,从而减少了运行时开销。以前的生产级技术只能复制短时间的执行,而ER可以复制任何重复出现的失败。因此,与现有工具不同,ER再现了完全可重现的执行,这些执行可以支持各种调试和可靠性用例。对于广泛的真实系统,ER平均产生0.3%(高达1.1%)的运行时监控开销,这使得它对于真实世界的部署是可行的。
Reproducing production failures is crucial for software reliability. Alas, existing bug reproduction approaches are not suitable for production systems because they are not simultaneously efficient, effective, and accurate. In this work, we survey prior techniques and show that existing approaches over-prioritize a subset of these properties, and sacrifice the remaining ones. As a result, existing tools do not enable the plethora of proposed failure reproduction use-cases (e.g., debugging, security forensics, fuzzing) for production failures.We propose Execution Reconstruction (ER), a technique that strikes a better balance between efficiency, effectiveness and accuracy for reproducing production failures. ER uses hardware-assisted control and data tracing to shepherd symbolic execution and reproduce failures. ER’s key novelty lies in identifying data values that are both inexpensive to monitor and useful for eliding the scalability limitations of symbolic execution. ER harnesses failure reoccurrences by iteratively performing tracing and symbolic execution, which reduces runtime overhead. Whereas prior production-grade techniques can only reproduce short executions, ER can reproduce any reoccuring failure. Thus, unlike existing tools, ER reproduces fully replayable executions that can power a variety of debugging and reliabilty use cases. ER incurs on average 0.3% (up to 1.1%) runtime monitoring overhead for a broad range of real-world systems, making it practical for real-world deployment.
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