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User feedback is imperative in improving software quality. In this paper, we explore the rich set of user feedback available for third party mobile applications as a way to extract new/changed requirements for next versions. A potential problem using this data is its volume and the time commitment involved in extracting new/changed requirements. Our goal is to alleviate part of the process through automatic topic extraction. We process user comments to extract the main topics mentioned as well as some sentences representative of those topics. This information can be useful for requirements engineers to revise the requirements for next releases. Our approach relies on adapting information retrieval techniques including topic modeling and evaluating them on different publicly available data sets. Results show that the automatically extracted topics match the manually extracted ones, while also significantly decreasing the manual effort.
Carreno et al. (Wed,) studied this question.