Improving software diagnosability via log enhancement

Author:

Yuan Ding1,Zheng Jing2,Park Soyeon2,Zhou Yuanyuan2,Savage Stefan3

Affiliation:

1. University of Illinois at Urbana-Champaign, Urbana, CA, USA

2. University of California, San Diego, San Diego, CA, USA

3. University of California San Diego, San Diego, CA, USA

Abstract

Diagnosing software failures in the field is notoriously difficult, in part due to the fundamental complexity of trouble-shooting 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 during diagnosis while imposing negligible overheads.

Publisher

Association for Computing Machinery (ACM)

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