DocumentCode :
2443547
Title :
Performance debugging in the large via mining millions of stack traces
Author :
Han, Shi ; Dang, Yingnong ; Ge, Song ; Zhang, Dongmei ; Xie, Tao
fYear :
2012
fDate :
2-9 June 2012
Firstpage :
145
Lastpage :
155
Abstract :
Given limited resource and time before software release, development-site testing and debugging become more and more insufficient to ensure satisfactory software performance. As a counterpart for debugging in the large pioneered by the Microsoft Windows Error Reporting (WER) system focusing on crashing/hanging bugs, performance debugging in the large has emerged thanks to available infrastructure support to collect execution traces with performance issues from a huge number of users at the deployment sites. However, performance debugging against these numerous and complex traces remains a significant challenge for performance analysts. In this paper, to enable performance debugging in the large in practice, we propose a novel approach, called StackMine, that mines callstack traces to help performance analysts effectively discover highly impactful performance bugs (e.g., bugs impacting many users with long response delay). As a successful technology-transfer effort, since December 2010, StackMine has been applied in performance-debugging activities at a Microsoft team for performance analysis, especially for a large number of execution traces. Based on real-adoption experiences of StackMine in practice, we conducted an evaluation of StackMine on performance debugging in the large for Microsoft Windows 7. We also conducted another evaluation on a third-party application. The results highlight substantial benefits offered by StackMine in performance debugging in the large for large-scale software systems.
Keywords :
data mining; operating systems (computers); program debugging; program diagnostics; program testing; software performance evaluation; Microsoft Windows 7; Microsoft Windows error reporting system; StackMine; callstack trace mining; crashing bugs; development-site testing; hanging bugs; large-scale software system; performance analysis; performance bugs; performance debugging; software release; technology-transfer effort; third-party application; Computer bugs; Data mining; Debugging; Delay; Performance analysis; Software systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2012 34th International Conference on
Conference_Location :
Zurich
ISSN :
0270-5257
Print_ISBN :
978-1-4673-1066-6
Electronic_ISBN :
0270-5257
Type :
conf
DOI :
10.1109/ICSE.2012.6227198
Filename :
6227198
Link To Document :
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