Statistical Debugging of Sampled Programs

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 correlated with crashes. This is accomplished by maximizing an appropriately defined utility function. It has analogies with intuitive debugging heuristics, and, as we demonstrate, is able to deal with various types of bugs that occur in real programs.

• Type: Conference
• Year: 2003
• Where: NIPS
• Authors: Alice X. Zheng, Michael I. Jordan, Ben Liblit, Alexander Aiken
• Keywords: Actual User Runs, Debugging, Intuitive Debugging Heuristics, NIPS 2003, NIPS 2007