We present a novel strategy for automatically debugging programs given sampled data from thousands of actual user runs. Our goal is to pinpoint those features that are most correl...
Alice X. Zheng, Michael I. Jordan, Ben Liblit, Ale...
We describe a statistical approach to software debugging in the presence of multiple bugs. Due to sparse sampling issues and complex interaction between program predicates, many g...
Alice X. Zheng, Michael I. Jordan, Ben Liblit, May...
Recently there has been a surge of interest in developing performance debugging tools to help programmers tune their applications for better memory performance [2, 4, 10]. These t...
Margaret Martonosi, Anoop Gupta, Thomas E. Anderso...
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
Statistical debugging aims to automate the process of isolating bugs by profiling several runs of the program and using statistical analysis to pinpoint the likely causes of failu...
Trishul M. Chilimbi, Ben Liblit, Krishna K. Mehra,...