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Automatic Software Fault Diagnosis by Exploiting Application Signatures

机译:利用应用程序签名自动进行软件故障诊断

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Application problem diagnosis in complex enterprise environments is a challenging problem, and contributes significantly to the growth in IT management costs. While application problems have a large number of possible causes, failures due to runtime interactions with the system environment (e.g., configuration files, resource limitations, access permissions) are one of the most common categories. Troubleshooting these problems requires extensive experience and time, and is very difficult to automate.rnIn this paper, we propose a black-box approach that can automatically diagnose several classes of application faults using applications' runtime behaviors. These behaviors along with various system states are combined to create signatures that serve as a baseline of normal behavior. When an application fails, the faulty behavior is analyzed against the signature to identify deviations from expected behavior and likely cause.rnWe implement a diagnostic tool based on this approach and demonstrate its effectiveness in a number of case studies with realistic problems in widely-used applications. We also conduct a number of experiments to show that the impact of the diagnostic tool on application performance (with some modifications of platform tracing facilities), as well as storage requirements for signatures, are both reasonably low.
机译:复杂企业环境中的应用程序问题诊断是一个具有挑战性的问题,并且极大地促进了IT管理成本的增长。尽管应用程序问题有很多可能的原因,但由于运行时与系统环境的交互(例如,配置文件,资源限制,访问权限)而导致的故障是最常见的类别之一。解决这些问题需要大量的经验和时间,并且很难实现自动化。在本文中,我们提出了一种黑盒方法,该方法可以使用应用程序的运行时行为自动诊断几类应用程序故障。将这些行为与各种系统状态结合在一起,以创建用作正常行为基线的签名。当应用程序失败时,将根据签名对错误行为进行分析,以识别与预期行为和可能原因的偏差。rn我们基于此方法实施诊断工具,并在许多案例研究中证明了其有效性,这些案例研究在广泛使用的应用程序中存在实际问题。我们还进行了许多实验,以表明诊断工具对应用程序性能的影响(对平台跟踪工具进行了一些修改)以及签名的存储要求都相当低。

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