Automated classification of software change messages by semi-supervised Latent Dirichlet Allocation
We present a semi-supervised LDA based approach to automatically classify the change messages. The model make use of the class label information with the software change domain knowledge. The latent topics in our model directly correspond to the software change class labels. Our model can be used to cross-project analysis.
change message lda software repositories mining semi-supervised topic modeling