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Production-Run Software Failure Diagnosis via Hardware Performance Counters
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BibTeX
@MISC{Arulraj_production-runsoftware,
author = {Joy Arulraj and Po-chun Chang and Guoliang Jin and Shan Lu},
title = {Production-Run Software Failure Diagnosis via Hardware Performance Counters},
year = {}
}
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Abstract
Sequential and concurrency bugs are widespread in deployed software. They cause severe failures and huge financial loss during production runs. Tools that diagnose production-run failures with low overhead are needed. The state-of-the-art diagnosis techniques use software instrumentation to sample program properties at run time and use off-line statistical analysis to identify properties most correlated with failures. Although promising, these techniques suffer from high run-time overhead, which is sometimes over 100%, for concurrency-bug failure diagnosis and hence are not suitable for production-run usage. We present PBI, a system that uses existing hardware performance counters to diagnose production-run failures caused by sequential and concurrency bugs with low overhead. PBI is designed based on several key observations. First, a few widely supported performance counter events can reflect a wide variety of common software bugs and can be monitored by hardware with almost no overhead. Second, the counter overflow interrupt supported by existing hardware and operating systems provides a natural and effective mechanism to conduct event sampling at user level. Third, the noise and non-determinism in interrupt delivery complements well with statistical processing. We evaluate PBI using 13 real-world concurrency and sequential bugs from representative open-source server, client, and utility programs, and 10 bugs from a widely used software-testing benchmark. Quantitatively, PBI can effectively diagnose failures caused by these bugs with a small overhead that is never higher than 10 %. Qualitatively, PBI does not require any change to software and presents a novel use of existing hardware performance counters.
Keyphrases
hardware performance counter production-run software failure diagnosis concurrency bug production-run failure low overhead interrupt delivery complement novel use utility program production run off-line statistical analysis state-of-the-art diagnosis technique run time small overhead software-testing benchmark sequential bug wide variety huge financial loss performance counter event user level representative open-source server high run-time overhead deployed software several key observation production-run usage effective mechanism severe failure real-world concurrency concurrency-bug failure diagnosis common software bug present pbi program property software instrumentation statistical processing
