TY - GEN
T1 - MisconfDoctor
T2 - 18th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2018
AU - Wang, Teng
AU - Liu, Xiaodong
AU - Li, Shanshan
AU - Liao, Xiangke
AU - Li, Wang
AU - Liao, Qing
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/2
Y1 - 2018/8/2
N2 - As software configurations continue to grow in complexity, misconfiguration has become one of major causes of software failure. Software configuration errors can have catastrophic consequences, seriously affecting the normal use of software and quality of service. And misconfiguration diagnosis faces many challenges, such as path-explosion problems and incomplete statistical data. Our study of the log that is generated in response to misconfigurations by six widely used pieces of software highlights some interesting characteristics. These observations have influenced the design of MisconfDoctor, a misconfiguration diagnosis tool via log-based configuration testing. Through comprehensive misconfiguration testing, MisconfDoctor first extracts log features for every misconfiguration and builds a feature database. When a system misconfiguration occurs, MisconfDoctor suggests potential misconfigurations by calculating the similarity of the new exception log to the feature database. We use manual and real-world error cases from Httpd, MySQL and PostgreSQL in order to evaluate the effectiveness of the tool. Experimental results demonstrate that the tool's accuracy reaches 85% when applied to manual-error cases, and 78% for real-world cases.
AB - As software configurations continue to grow in complexity, misconfiguration has become one of major causes of software failure. Software configuration errors can have catastrophic consequences, seriously affecting the normal use of software and quality of service. And misconfiguration diagnosis faces many challenges, such as path-explosion problems and incomplete statistical data. Our study of the log that is generated in response to misconfigurations by six widely used pieces of software highlights some interesting characteristics. These observations have influenced the design of MisconfDoctor, a misconfiguration diagnosis tool via log-based configuration testing. Through comprehensive misconfiguration testing, MisconfDoctor first extracts log features for every misconfiguration and builds a feature database. When a system misconfiguration occurs, MisconfDoctor suggests potential misconfigurations by calculating the similarity of the new exception log to the feature database. We use manual and real-world error cases from Httpd, MySQL and PostgreSQL in order to evaluate the effectiveness of the tool. Experimental results demonstrate that the tool's accuracy reaches 85% when applied to manual-error cases, and 78% for real-world cases.
KW - Configuration testing
KW - Exception log
KW - Misconfguration
UR - https://www.scopus.com/pages/publications/85052290696
U2 - 10.1109/QRS.2018.00014
DO - 10.1109/QRS.2018.00014
M3 - 会议稿件
AN - SCOPUS:85052290696
SN - 9781538677575
T3 - Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security, QRS 2018
SP - 1
EP - 12
BT - Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security, QRS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 July 2018 through 20 July 2018
ER -