The Unreasonable Effectiveness of Traditional Information Retrieval in Crash Report Deduplication

Abstract

Organizations like Mozilla, Microsoft, and Apple are floodedwith thousands of automated crash reports per day. Although crash reports contain valuable information for debugging, there are often too many for developers to examineindividually. Therefore, in industry, crash reports are oftenautomatically grouped together in buckets. Ubuntu’s repository contains crashes from hundreds of software systemsavailable with Ubuntu. A variety of crash report bucketing methods are evaluated using data collected by Ubuntu’sApport automated crash reporting system. The trade-off between precision and recall of numerous scalable crash deduplication techniques is explored. A set of criteria that acrash deduplication method must meet is presented and several methods that meet these criteria are evaluated on anew dataset. The evaluations presented in this paper showthat using off-the-shelf information retrieval techniques, thatwere not designed to be used with crash reports, outperformother techniques which are specifically designed for the taskof crash bucketing at realistic industrial scales. This researchindicates that automated crash bucketing still has a lot ofroom for improvement, especially in terms of identifier tokenization.