MINING THE COHERENCE OF GNOME BUG REPORTS WITH STATISTICAL TOPIC MODELS

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We adapt Latent Dirichlet Allocation to the problem of mining bug reports in order to define a new information-theoretic measure of coherence. We then apply our technique to a snapshot of the GNOME Bugzilla database consisting of 431,863 bug reports for multiple software projects. In addition to providing an unsupervised means for modeling report content, our results indicate substantial promise in applying statistical text mining algorithms for estimating bug report quality. Complete results are available from our supplementary materials.Â