Debugging Crashes using Continuous Contrast Set Mining
Facebook operates a family of services used by over 2 billion people daily on a huge variety of mobile devices. Many devices are configured to upload crash reports should the app crash for any reason. Engineers monitor and triage millions of crash reports logged each day to check for bugs, regressions, and any other quality problems. Debugging groups of crashes is a manually intensive process that requires deep domain expertise and close inspection of traces and code, often under time constraints.
We use contrast set mining, a form of discriminative pattern mining, to learn what distinguishes one group of crashes from another. Prior works focus on discretization to apply contrast mining to continuous data. We propose the first direct application of contrast learning to continuous data, without the need for discretization. We also define a weighted anomaly score that unifies continuous and categorical contrast sets while mitigating bias, as well as uncertainty measures that communicate confidence to developers. We demonstrate the value of our novel statistical improvements by applying it on a challenging dataset, user navigation event sequences.
Wed 8 Jul Times are displayed in time zone: (UTC) Coordinated Universal Time change
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Jinhan Kim, Valeriy SavchenkoIvannikov Institute for System Programming of the RAS, Kihyuck ShinSamsung Electronics, Konstantin SorokinIvannikov Institute for System Programming of the RAS, Hyunseok JeonSamsung Electronics, Georgiy PankratenkoIvannikov Institute for System Programming of the RAS, Sergey MarkovIvannikov Institute for System Programming of the RAS, Chul-Joo KimSamsung Electronics
|01:29 - 01:37|
Haijun WangAnt Financial Services Group, China; CSSE, Shenzhen University, China, Yun LinNational University of Singapore, Zijiang YangWestern Michigan University, Jun SunSingapore Management University, Yang LiuNanyang Technological University, Singapore, Jin Song DongNational University of Singapore, Qinghua ZhengXi'an Jiaotong University, Ting LiuXi'an Jiaotong University
|01:37 - 01:45|
Ming WenHuazhong University of Science and Technology, China, Junjie ChenTianjin University, China, Yongqiang TIANThe Hong Kong University of Science and Technology, Rongxin WuDepartment of Cyber Space Security, Xiamen University, Dan HaoPeking University, Shi HanMicrosoft Research Asia, Shing-Chi CheungDepartment of Computer Science and Engineering, The Hong Kong University of Science and Technology
|01:45 - 01:53|
Ivan BeschastnikhComputer Science, University of British Columbia, Perry LiuUniversity of British Columbia, Albert XingUniversity of British Columbia, Patty WangUniversity of British Columbia, Yuriy BrunUniversity of Massachusetts Amherst, Michael D. ErnstUniversity of Washington, USADOI Pre-print
|01:53 - 02:01|