Understanding Log Lines Using Development Knowledge
Authors -
Weiyi, Shang;
Meiyappan, Nagappan;
Ahmed, E. Hassan and
Zhen, Ming Jiang
Venue -
In Proceedings of the 30th IEEE International Conference on Software Maintenance and Evolution (ICSME 2014), Victoria, Canada, October 1 - 3, 2014
Related Tags -
Abstract -
Logs are generated by output statements that developers
insert into the code. By recording the system behaviour
during runtime, logs play an important role in the maintenance
of large software systems. The rich nature of logs has introduced
a new market of log management applications (e.g., Splunk, XpoLog and logstash) that assist in storing, querying and analyzing
logs. Moreover, recent research has demonstrated the
importance of logs in operating, understanding and improving
software systems. Thus log maintenance is an important task
for the developers. However, all too often practitioners (i.e., operators and administrators) are left without any support to
help them unravel the meaning and impact of specific log lines.
By spending over 100 human hours and manually examining
all the email threads in the mailing list for three open source
systems (Hadoop, Cassandra and Zookeeper) and performing web
search on sampled logging statements, we found 15 email inquiries
and 73 inquiries from web search about different log lines. We
identified that five types of development knowledge that are
often sought from the logs by practitioners: meaning, cause, context, impact and solution. Due to the frequency and nature
of log lines about which real customers inquire, documenting
all the log lines or identifying which ones to document is not
efficient. Hence in this paper we propose an on-demand approach, which associates the development knowledge present in various
development repositories (e.g., code commits and issues reports)
with the log lines. Our case studies show that the derived
development knowledge can be used to resolve real-life inquiries
about logs.
Preprint -
PDF
BibTex -
@article{Shang2014_2,
author = {Weiyi, Shang and Meiyappan, Nagappan and Ahmed, E. Hassan and Zhen, Ming Jiang},
keyword = {Defect Prediction, Log File Analysis},
title = {Understanding Log Lines Using Development Knowledge},
type = {conference},
venue = {In Proceedings of the 30th IEEE International Conference on Software Maintenance and Evolution (ICSME 2014), Victoria, Canada, October 1 - 3, 2014}
}