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MSR 2019
Sun 26 - Mon 27 May 2019 Montreal, QC, Canada
co-located with ICSE 2019
Mon 27 May 2019 15:01 - 15:07 at Place du Canada - Session IX: Traceability Chair(s): Francisco Servant

Logs are widely used as a source of information to understand the activity of computer systems and to monitor their health and stability. However, most log analysis techniques require the link between the log messages in the raw log file and the log statements in the source code that produce them. Several solutions have been proposed to solve this non-trivial challenge, of which the approach based on static analysis reaches the highest accuracy. We, at Adyen, implemented the state-of-the-art research on log parsing in our logging environment and evaluated their accuracy and performance. Our results show that, with some adaptation, the current static analysis techniques are highly efficient and performant. In other words, ready for use.

Mon 27 May

Displayed time zone: Eastern Time (US & Canada) change

14:45 - 15:30
Session IX: TraceabilityMSR 2019 Technical Papers at Place du Canada
Chair(s): Francisco Servant Virginia Tech
14:45
15m
Full-paper
Predicting Co-Changes between Functionality Specifications and Source Code in Behavior Driven Development
MSR 2019 Technical Papers
Aidan Z.H. Yang Queen's University, Canada, Daniel Alencar Da Costa Queen's University, Kingston, Ontario, Ying Zou Queen's University, Kingston, Ontario
15:01
6m
Short-paper
Tracing Back Log Data to its Log Statement: From Research to Practice
MSR 2019 Technical Papers
Daan Schipper , Maurício Aniche Delft University of Technology, Netherlands, Arie van Deursen Delft University of Technology
Pre-print
15:08
6m
Short-paper
Beyond GumTree: A hybrid approach to generate edit scripts
MSR 2019 Technical Papers
Junnosuke Matsumoto , Yoshiki Higo Osaka University, Shinji Kusumoto Osaka University
Pre-print
15:15
6m
Short-paper
The Impact of Systematic Edits in History Slicing
MSR 2019 Technical Papers
Ryosuke Funaki , Shinpei Hayashi Tokyo Institute of Technology, Motoshi Saeki Tokyo Institute of Technology
Pre-print
15:22
6m
Short-paper
Scalable Software Merging Studies with MERGANSER
MSR 2019 Technical Papers
Moein Owhadi-Kareshk , Sarah Nadi University of Alberta