Improving Software Diagnosability via Log Enhancement

  • Authors:

  • Ding Yuan;Jing Zheng;Soyeon Park;Yuanyuan Zhou;Stefan Savage

  • Affiliations:

  • University of Illinois at Urbana-Champaign and University of California, San Diego;University of California, San Diego;University of California, San Diego;University of California, San Diego;University of California, San Diego

  • Venue:
  • ACM Transactions on Computer Systems (TOCS) - Special Issue APLOS 2011
  • Year:
  • 2012

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Abstract

Diagnosing software failures in the field is notoriously difficult, in part due to the fundamental complexity of troubleshooting any complex software system, but further exacerbated by the paucity of information that is typically available in the production setting. Indeed, for reasons of both overhead and privacy, it is common that only the run-time log generated by a system (e.g., syslog) can be shared with the developers. Unfortunately, the ad-hoc nature of such reports are frequently insufficient for detailed failure diagnosis. This paper seeks to improve this situation within the rubric of existing practice. We describe a tool, LogEnhancer that automatically “enhances” existing logging code to aid in future post-failure debugging. We evaluate LogEnhancer on eight large, real-world applications and demonstrate that it can dramatically reduce the set of potential root failure causes that must be considered while imposing negligible overheads.