评估系统调用软错误可靠性的故障注入方法

R. Amarnath, S. Bhat, Peter Munk, E. Thaden
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引用次数: 10

摘要

为了满足高度自动化驾驶的吞吐量需求,中央处理器(cpu)放弃了可靠性,转而追求性能。这样的CPU通常不包括广泛的硬件实现的可靠性措施,例如,同步CPU内核。与此同时,兼容POSIX(包括类linux)的操作系统(os)在这类复杂的汽车系统中越来越受欢迎,例如即将推出的AUTOSAR Adaptive标准就是基于POSIX[1]。在此类系统中,对操作系统等关键软件组件的故障分析成为重要的可靠性资产。我们通过将随机硬件故障注入CPU来确定给定操作系统的鲁棒性,并测量这些故障在操作系统中传播的程度,以显示为应用程序级副作用。在本文中,我们提出了一个基于qemu的故障注入框架,该框架模拟了Linux 4.10系统调用执行过程中x86寄存器中的位翻转,并在应用程序级别对其影响进行了分类。结果表明,对于clone、futex、mmap、mprotect和pipe系统调用,在448万个注入故障中,平均76.3%是良性的。我们的实验还表明,程序计数器和堆栈指针(在内存操作的情况下)是最易受影响的寄存器。我们的度量有助于指导软件实现的硬件容错(SIHFT)度量的适当部署。重新评估实施的高频交易措施可能被用作安全性的论据。
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A Fault Injection Approach to Evaluate Soft-Error Dependability of System Calls
Central Processing Units (CPUs) that satisfy the throughput demands of highly automated driving trade reliability off for performance. Such CPUs often do not include extensive hardware-implemented reliability measures e. g., lockstep CPU cores. At the same time, POSIX-compliant (including Linux-like) operating systems (OSs) become increasingly popular for such complex automotive systems, e. g., the upcoming AUTOSAR Adaptive standard is based on POSIX [1]. In such systems, the fault analysis of critical software components such as the OS becomes an important dependability asset. We determine the robustness of a given OS by injecting random hardware faults into the CPU and measure the extent to which these faults propagate through the OS in order to manifest as application level side effects. In this paper, we present our QEMU-based fault injection framework that simulates bit flips in x86 registers during the execution of the system calls of Linux 4.10 and classifies their effects at the application level. Our results show that for the clone, futex, mmap, mprotect, and pipe syscalls in average 76.3% of the 4.48 million injected faults are benign.Our experiments also show that the program counter and stack pointer (in case of memory operations) are the most susceptible registers. Our measurements help to guide the appropriate deployment of software-implemented hardware fault-tolerance (SIHFT) measures. Re-evaluation of the implemented SIHFT measures can be potentially used as an argument for safety.
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Message from the WoSoCer 2018 Workshop Chairs Software Aging and Rejuvenation in the Cloud: A Literature Review Spectrum-Based Fault Localization for Logic-Based Reasoning [Title page iii] Software Reliability Assessment: Modeling and Algorithms
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