Implementation of Android Application Crash Clustering System Applied on Douyin Crash Data
With the expansion of active users of applications,the amount of crashes has also experienced large-scale growth.In order to achieve efficient analysis of crashes,a system that can accurately cluster crashes is required.We present a two-level crash clustering method aiming at Android App Crash based on crash features.Firstly,from the collected crash reporting stacks,the types of Java crashes,exception descriptions,business code lines,and system code lines are analyzed.Then,the interference information in the exception description is standardized to obtain the standardized exception description,business code lines are decomposed to obtain root case code line and the full exception code path is resolved from business code lines and system code lines.Finally,the crash type,standardized exception description and business code root cause are used to calculate the first hash value,which is used to cluster the crashes into the first level list.The crash type,standardized exception description and full code path are used to calculate the second hash value,which is used to cluster the crashes into the second level list.The system has been deployed in the internal APM system of one big internet company,and has been validated through large-scale testing in applications such as Douyin and Toutiao,meeting the demand for accurate clustering of crashes.
万方数据
维普
