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ASE 2023
(
series
) /
NIER Track
/
Log Parsing: How Far Can ChatGPT Go?
Who
Van-Hoang Le
,
Hongyu Zhang
Track
ASE 2023 NIER Track
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When
Tue 12 Sep 2023 10:42 - 10:54 at
Room D
-
Infrastructure, Build, and Logs
Chair(s):
Fatemeh Hendijani Fard
,
Arie van Deursen
Link to Preprint
https://arxiv.org/pdf/2306.01590.pdf
Van-Hoang Le
The University of Newcastle
Vietnam
Hongyu Zhang
Chongqing University
China
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Session Program
Tue 12 Sep
Displayed time zone:
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change
10:30 - 12:00
Infrastructure, Build, and Logs
Research Papers
/
Industry Showcase (Papers)
/
NIER Track
/
Journal-first Papers
at
Room D
Chair(s):
Fatemeh Hendijani Fard
University of British Columbia
,
Arie van Deursen
Delft University of Technology
10:30
12m
Talk
Are They All Good? Studying Practitioners' Expectations on the Readability of Log Messages
Research Papers
Zhenhao Li
Concordia University
,
An Ran Chen
University of Alberta
,
Xing Hu
Zhejiang University
,
Xin Xia
Huawei Technologies
,
Tse-Hsun (Peter) Chen
Concordia University
,
Weiyi Shang
University of Waterloo
Pre-print
10:42
12m
Talk
Log Parsing: How Far Can ChatGPT Go?
NIER Track
Van-Hoang Le
The University of Newcastle
,
Hongyu Zhang
Chongqing University
Pre-print
10:54
12m
Talk
On the usage, co-usage and migration of CI/CD tools: a qualitative analysis
Journal-first Papers
Pooya Rostami Mazrae
University of Mons
,
Tom Mens
University of Mons
11:06
12m
Talk
Predicting Compilation Resources for Adaptive Build in an Industrial Setting
Industry Showcase (Papers)
Junhao Hu
Peking University
,
Chaozheng Wang
The Chinese University of Hong Kong
,
Hailiang Huang
Tencent Inc.
,
Huang Luo
Tencent Inc.
,
Yu Jin
Tencent Inc.
,
Yuetang Deng
Tencent
,
Tao Xie
Peking University
11:30
12m
Talk
What Quality Aspects Influence the Adoption of Docker Images?
Journal-first Papers
Giovanni Rosa
University of Molise
,
Simone Scalabrino
University of Molise
,
Gabriele Bavota
Software Institute, USI Università della Svizzera italiana
,
Rocco Oliveto
University of Molise
Link to publication
Media Attached
11:42
12m
Talk
LogOnline: A Semi-supervised Log-based Anomaly Detector Aided with Online Learning Mechanism
Recorded talk
Research Papers
Xuheng Wang
Tsinghua University
,
Jiaxing Song
Tsinghua University
,
Xu Zhang
Microsoft Research
,
Junshu Tang
Shanghai Jiao Tong University
,
Weihe Gao
Tsinghua University
,
Qingwei Lin
Microsoft
,
Xuheng Wang
Tsinghua University
Link to publication
DOI
Media Attached
x
Wed 18 Dec 15:09