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Probabilistic Graph Models for Debugging Software
by
Laura Dietz
,
Rg Machine Learning
,
Valentin Dallmeier
BibTeX
@MISC{Dietz_probabilisticgraph,
author = {Laura Dietz and Rg Machine Learning and Valentin Dallmeier},
title = {Probabilistic Graph Models for Debugging Software},
year = {}
}
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Abstract
Of all software development activities, debugging—locating the defective source code statements that cause a failure—can be by far the most time-consuming. We employ probabilistic modeling to support programmers in finding defective code. Most defects are identifiable in control flow graphs of software traces. A trace is represented by a sequence of code positions (line numbers in source
