Contextual analysis of program logs for understanding system behaviors

Qiang Fu, Jian Guang Lou, Qingwei Lin, Rui Ding, Dongmei Zhang, Tao Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding the behaviors of a software system is very important for performing daily system maintenance tasks. In practice, one way to gain knowledge about the runtime behavior of a system is to manually analyze system logs collected during the system executions. With the increasing scale and complexity of software systems, it has become challenging for system operators to manually analyze system logs. To address these challenges, in this paper, we propose a new approach for contextual analysis of system logs for understanding a system's behaviors. In particular, we first use execution patterns to represent execution structures reflected by a sequence of system logs, and propose an algorithm to mine execution patterns from the program logs. The mined execution patterns correspond to different execution paths of the system. Based on these execution patterns, our approach further learns essential contextual factors (e.g., the occurrences of specific program logs with specific parameter values) that cause a specific branch or path to be executed by the system. The mining and learning results can help system operators to understand a software system's runtime execution logic and behaviors during various tasks such as system problem diagnosis. We demonstrate the feasibility of our approach upon two real-world software systems (Hadoop and Ethereal).

Original languageEnglish (US)
Title of host publication2013 10th Working Conference on Mining Software Repositories, MSR 2013 - Proceedings
Pages397-400
Number of pages4
DOIs
StatePublished - Dec 9 2013
Externally publishedYes
Event10th International Working Conference on Mining Software Repositories, MSR 2013 - San Francisco, CA, United States
Duration: May 18 2013May 19 2013

Publication series

NameIEEE International Working Conference on Mining Software Repositories
ISSN (Print)2160-1852
ISSN (Electronic)2160-1860

Other

Other10th International Working Conference on Mining Software Repositories, MSR 2013
CountryUnited States
CitySan Francisco, CA
Period5/18/135/19/13

Keywords

  • Contextual analysis
  • Log analysis
  • Understanding system behaviors

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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