Automatic Abnormal Log Detection by Analyzing Log History for Providing Debugging InsightSEIP
As the size of software becomes larger and more complex, finding the cause of defects becomes increasingly difficult. Moreover, it is very hard to reproduce defects when many components such as processes in platform environment or devices in IoT environment are involved. In this case, analyzing logs are the only way to get debugging insights, but manual log analysis is highly labor intensive work. In this paper, we propose a new log analysis system called historian which runs based on history of test logs. Our system first computes importance and noise scores of each log line by using statistical text mining techniques to find abnormal log lines, and then highlights log lines based on computed scores for providing debugging insights. We applied historian to Tizen Native API test logs, and our tool highlighted only about 4% log lines in average. We also provided highlighted failed logs to Tizen developers and the developers said that failure related log lines were highlighted well. These experimental results show that our system effectively highlights abnormal log lines and provides debugging insights to developers.
Wed 8 JulDisplayed time zone: (UTC) Coordinated Universal Time change
01:05 - 02:05 | P12-Testing and DebuggingJournal First / Software Engineering in Practice at Silla Chair(s): Taeksu Kim Samsung Research, Samsung Electronics | ||
01:05 12mTalk | Debugging Crashes using Continuous Contrast Set MiningSEIP Software Engineering in Practice Rebecca Qian Facebook, Inc., Yang Yu Purdue University, Wonhee Park Facebook, Inc., Vijayaraghavan Murali Facebook, Inc., Stephen J Fink Facebook, Satish Chandra Facebook | ||
01:17 12mTalk | Automatic Abnormal Log Detection by Analyzing Log History for Providing Debugging InsightSEIP Software Engineering in Practice Jinhan Kim , Valeriy Savchenko Ivannikov Institute for System Programming of the RAS, Kihyuck Shin Samsung Electronics, Konstantin Sorokin Ivannikov Institute for System Programming of the RAS, Hyunseok Jeon Samsung Electronics, Georgiy Pankratenko Ivannikov Institute for System Programming of the RAS, Sergey Markov Ivannikov Institute for System Programming of the RAS, Chul-Joo Kim Samsung Electronics | ||
01:29 8mTalk | Explaining Regressions via Alignment Slicing and MendingJ1 Journal First Haijun Wang Ant Financial Services Group, China; CSSE, Shenzhen University, China, Yun Lin National University of Singapore, Zijiang Yang Western Michigan University, Jun Sun Singapore Management University, Yang Liu Nanyang Technological University, Singapore, Jin Song Dong National University of Singapore, Qinghua Zheng Xi'an Jiaotong University, Ting Liu Xi'an Jiaotong University | ||
01:37 8mTalk | Historical Spectrum based Fault LocalizationJ1 Journal First Ming Wen Huazhong University of Science and Technology, China, Junjie Chen Tianjin University, China, Yongqiang TIAN The Hong Kong University of Science and Technology, Rongxin Wu Department of Cyber Space Security, Xiamen University, Dan Hao Peking University, Shi Han Microsoft Research Asia, Shing-Chi Cheung Department of Computer Science and Engineering, The Hong Kong University of Science and Technology | ||
01:45 8mTalk | Visualizing distributed system executionsJ1 Journal First Ivan Beschastnikh Computer Science, University of British Columbia, Perry Liu University of British Columbia, Albert Xing University of British Columbia, Patty Wang University of British Columbia, Yuriy Brun University of Massachusetts Amherst, Michael D. Ernst University of Washington, USA DOI Pre-print | ||
01:53 8mTalk | An Integration Test Order Strategy to Consider Control CouplingJ1 Journal First Shujuan Jiang China University of Mining and Technology, Miao ZHANG City University of Hong Kong, Yanmei ZHANG China University of Mining and Technology, Rongcun Wang China University of Mining and Technology, Qiao YU Jiangsu Normal University, Jacky Keung City University of Hong Kong | ||