Software often crashes. Once a crash happens, a crash report could be sent to software developers for investigation upon user permission. To facilitate efficient handling of crashes, crash reports received by Microsoft's Windows Error Reporting (WER) system are organized into a set of “buckets”. Each bucket contains duplicate crash reports that are deemed as manifestations of the same bug. The bucket information is important for prioritizing efforts to resolve crashing bugs. To improve the accuracy of bucketing, we propose ReBucket, a method for clustering crash reports based on call stack matching. ReBucket measures the similarities of call stacks in crash reports and then assigns the reports to appropriate buckets based on the similarity values. We evaluate ReBucket using crash data collected from five widely-used Microsoft products. The results show that ReBucket achieves better overall performance than the existing methods. On average, the F-measure obtained by ReBucket is about 0.88.

Perhaps surprisingly, no practical performance models exist for popular (and complex) client applications such as Adobe's Creative Suite, Microsoft's Office and Visual Studio, Mozilla, Halo 3, etc. There is currently no tool that automatically answers program developers', IT administrators' and end-users' simple what-if questions like "what happens to the performance of my favorite application X if I upgrade from Windows Vista to Windows 7?". This paper describes our approach towards constructing practical, versatile performance models to address this problem. The goal is to have these models be useful for application developers to help expand application testing coverage and for IT administrators to assist with understanding the performance consequences of a software, hardware or configuration change.