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Ben Liblit

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2 papers

2 author rows

ICML Conference 2006 Conference Paper

Statistical debugging: simultaneous identification of multiple bugs

Alice X. Zheng
Michael I. Jordan
Ben Liblit
Mayur Naik
Alexander Aiken

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 generic off-the-shelf algorithms fail to select useful bug predictors. Taking inspiration from bi-clustering algorithms, we propose an iterative collective voting scheme for the program runs and predicates. We demonstrate successful debugging results on several real world programs and a large debugging benchmark suite.

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NeurIPS Conference 2003 Conference Paper

Statistical Debugging of Sampled Programs

Alice Zheng
Michael Jordan
Ben Liblit
Alex Aiken

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.

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