TY - GEN
T1 - Fault Localization in Server-Side Applications Using Spectrum-Based Fault Localization
AU - Sha, Yoshitomo
AU - Nagura, Masataka
AU - Takada, Shingo
N1 - Funding Information:
ACKNOWLEDGEMENTS This research was partially supported by JSPS KAKENHI grant number 20K11758, and partially by the grant from Nanzan University Pache Research Subsidy I-A-2 for the 2021 academic year.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Today's software has a very complex structure with multiple components, making it difficult to identify the cause of a fault. The process of identifying the cause of a fault may include referring to the logs from the system if they exist. But large and complex systems may generate a huge amount of logs, making the task of finding the important log messages to be a tedious task. In the case of systems that require continuous operation, the cause of faults must be identified quickly in an efficient manner. In this paper, we propose a method that identifies the log messages that are key for finding faults in server-side applications that has a tiered structure, such as LAMP (Linux, Apache, MySQL, PHP), and outputs logs (including traces during operation). The key part of our proposed approach is the application of Spectrum-Based Fault Localization (SBFL) to log files.
AB - Today's software has a very complex structure with multiple components, making it difficult to identify the cause of a fault. The process of identifying the cause of a fault may include referring to the logs from the system if they exist. But large and complex systems may generate a huge amount of logs, making the task of finding the important log messages to be a tedious task. In the case of systems that require continuous operation, the cause of faults must be identified quickly in an efficient manner. In this paper, we propose a method that identifies the log messages that are key for finding faults in server-side applications that has a tiered structure, such as LAMP (Linux, Apache, MySQL, PHP), and outputs logs (including traces during operation). The key part of our proposed approach is the application of Spectrum-Based Fault Localization (SBFL) to log files.
KW - Fault localization
KW - LAMP
KW - Log analysis
UR - http://www.scopus.com/inward/record.url?scp=85135851736&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135851736&partnerID=8YFLogxK
U2 - 10.1109/SANER53432.2022.00131
DO - 10.1109/SANER53432.2022.00131
M3 - Conference contribution
AN - SCOPUS:85135851736
T3 - Proceedings - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022
SP - 1139
EP - 1146
BT - Proceedings - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022
Y2 - 15 March 2022 through 18 March 2022
ER -