Toward generating reducible replay logs

  • Authors:

  • Kyu Hyung Lee;Yunhui Zheng;Nick Sumner;Xiangyu Zhang

  • Affiliations:

  • Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA

  • Venue:
  • Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
  • Year:
  • 2011

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Abstract

Logging and replay is important to reproducing software failures and recovering from failures. Replaying a long execution is time consuming, especially when replay is further integrated with runtime techniques that require expensive instrumentation, such as dependence detection. In this paper, we propose a technique to reduce a replay log while retaining its ability to reproduce a failure. While traditional logging records only system calls and signals, our technique leverages the compiler to selectively collect additional information on the fly. Upon a failure, the log can be reduced by analyzing itself. The collection is highly optimized. The additional runtime overhead of our technique, compared to a plain logging tool, is trivial (2.61% average) and the size of additional log is comparable to the original log. Substantial reduction can be cost-effectively achieved through a search based algorithm. The reduced log is guaranteed to reproduce the failure.