Synoptic: Studying logged behavior with inferred models"/> Synoptic: Studying logged behavior with inferred models"/>
@inproceedings{Beschastnikh11tool-demo-fse,
author = {Ivan Beschastnikh and Jenny Abrahamson and Yuriy Brun and Michael
D. Ernst},
title =
{Synoptic:
{Studying} logged behavior with inferred models},
booktitle = {Proceedings of the 8th Joint Meeting of the European Software
Engineering Conference and ACM SIGSOFT Symposium on the Foundations of
Software Engineering Tool Demonstration Track (ESEC/FSE)},
venue = {ESEC/FSE Demo},
month = {September},
year = {2011},
date = {5--9},
pages = {448--451},
address = {Szeged, Hungary},
doi = {10.1145/2025113.2025188},
accept = {$\frac{14}{30} \approx 47\%$},
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.},
note = {DOI:
10.1145/2025113.2025188},
fundedBy = {NSF CNS-0937060 to the CRA for the CIFellows Project,
NSF CNS-0963754, NSF CCF-1016701},
}