``Automatic software fault diagnosis by exploiting application signatures" Xiaoning Ding, Hai Huang, Yaoping Ruan, Anees Shaikh, and Xiaodong Zhang Proceedings of 22nd USENIX Conference on Large Installation System Administration, (LISA'08), San Diego, California, November 9-14, 2008. Abstract 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. In 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. We 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.Back to the Publication Page.
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