Web error classification and analysis for reliability improvement

  • Authors:
  • Li Ma;Jeff Tian

  • Affiliations:
  • Southern Methodist University, Computer Science and Engineering Department, Dallas, Texas 75275, USA;Southern Methodist University, Computer Science and Engineering Department, Dallas, Texas 75275, USA

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2007

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Abstract

In this paper, we adapt an existing defect classification and analysis framework, orthogonal defect classification (ODC), to analyze web errors and identify problematic areas for focused reliability improvement. Based on information extracted from existing web server logs, web errors are classified according to their response code, file type, referrer type, agent type, and observation time. We also introduce an analysis procedure to identify high-risk/high-leverage sub-classes of problems and consolidate analysis results to recommend appropriate followup actions. Results applying our approach to the www.seas.smu.edu and www.kde.org web sites are included to demonstrate its applicability and effectiveness.