Precomputing possible configuration error diagnoses

  • Authors:

  • Ariel Rabkin;Randy Katz

  • Affiliations:

  • EECS Department, UC Berkeley, California, USA;EECS Department, UC Berkeley, California, USA

  • Venue:
  • ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
  • Year:
  • 2011

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Abstract

Complex software packages, particularly systems software, often require substantial customization before being used. Small mistakes in configuration can lead to hard-todiagnose error messages. We demonstrate how to build a map from each program point to the options that might cause an error at that point. This can aid users in troubleshooting these errors without any need to install or use additional tools. Our approach relies on static dataflow analysis, meaning all the analysis is done in advance. We evaluate our work in detail on two substantial systems, Hadoop and the JChord program analysis toolkit, using failure injection and also by using log messages as a source of labeled program points. When logs and stack traces are available, they can be incorporated into the analysis. This reduces the number of false positives by nearly a factor of four for Hadoop, at the cost of approximately one minute's work per unique query