Synoptic: studying logged behavior with inferred models

  • Authors:
  • Ivan Beschastnikh;Jenny Abrahamson;Yuriy Brun;Michael D. Ernst

  • Affiliations:
  • University of Washington, Seattle, WA, USA;University of Washington, Seattle, WA, USA;University of Washington, Seattle, WA, USA;University of Washington, Seattle, WA, USA

  • Venue:
  • Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
  • Year:
  • 2011

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Abstract

Logging is a powerful method for capturing program activity and state during an execution. However, log inspection remains a tedious activity, with developers often piecing together what went on from multiple log lines and across many files. This paper describes Synoptic, a tool that takes logs as input and outputs a finite state machine that models the process generating the logs. The paper overviews the model inference algorithms. Then, it describes the Synoptic tool, which is designed to support a rich log exploration workflow.