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MSR 2019
Sun 26 - Mon 27 May 2019 Montreal, QC, Canada
co-located with ICSE 2019

Software repositories contain large amounts of textual data, ranging from source code comments and issue descriptions to questions, answers, and comments on Stack Overflow. To make sense of this textual data, topic modelling is frequently used as a text-mining tool for the discovery of hidden semantic structures in text bodies. Latent Dirichlet allocation (LDA) is a commonly used topic model that aims to explain the structure of a corpus by grouping texts. LDA requires multiple parameters to work well, and there are only rough and sometimes conflicting guidelines available on how these parameters should be set. In this paper, we contribute (i) a broad study of parameters to arrive at good local optima for GitHub and Stack Overflow text corpora, (ii) an a-posteriori characterisation of text corpora related to eight programming languages, and (iii) an analysis of corpus feature importance via per-corpus LDA configuration. We find that (1) popular rules of thumb for topic modelling parameter configuration are not applicable to the corpora used in our experiments, (2) corpora sampled from GitHub and Stack Overflow have different characteristics and require different configurations to achieve good model fit, and (3) we can predict good configurations for unseen corpora reliably. These findings support researchers and practitioners in efficiently determining suitable configurations for topic modelling when analysing textual data contained in software repositories.

Sun 26 May

msr-2019-Paper-Presentations
11:55 - 12:30: MSR 2019 Paper Presentations - Session III: Representations for Mining (Part 2) at Place du Canada
Chair(s): Nicole NovielliUniversity of Bari
msr-2019-papers11:55 - 12:10
Full-paper
Eeshita Biswas, K. Vijay-Shanker, Lori PollockUniversity of Delaware, USA
Pre-print
msr-2019-Data-Showcase12:10 - 12:16
Talk
Musfiqur RahmanConcordia University, Montreal, Canada, Peter RigbyConcordia University, Montreal, Canada, Dharani PalaniConcordia University, Tien N. NguyenUniversity of Texas at Dallas
msr-2019-papers12:16 - 12:31
Full-paper
Christoph TreudeThe University of Adelaide, Markus Wagner
Pre-print