Towards automatic requirements elicitation from feedback comments: Extracting requirements topics using LDA

Abstract

Feedback comments, such as mailing lists and reviews, contain beneficial suggestion for software developers. Recently, developers have received more and more feedback comments; but it is still difficult to extract beneficial comments from a large amount of e-mail message or reviews. Latent Dirichlet Allocation (LDA) is a promising way of topic modeling, which classifies documents according to implicit multiple topics. In this paper, we tried to apply a requirements elicitation based on LDA to two different sources, i.e., Apache Commons User List and App Store reviews, and discuss the feasibility of this approach. An interesting finding was that some usual stop words indicated requirements description. This suggests that these words should be removed from the stop word list before applying LDA.