Performance Debugging in the Large via Mining Millions of Stack Traces.

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Bibliographic Details
Title:	Performance Debugging in the Large via Mining Millions of Stack Traces.
Authors:	Han, Shi¹ shihan@microsoft.com, Dang, Yingnong¹ yidang@microsoft.com, Ge, Song¹ songge@microsoft.com, Zhang, Dongmei¹ dongmeiz@microsoft.com, Xie, Tao² xie@csc.ncsu.edu
Source:	ICSE: International Conference on Software Engineering. Feb2012, p145-155. 11p.
Subjects:	Debugging, Computer system failure prevention, Data mining, Data security failures, Computer software, Microsoft Corp., Computer networks
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. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
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. [ABSTRACT FROM AUTHOR]