Using findings from the literature review, we then present a reference model that relates features of app review mining tools to specific software engineering tasks supporting requirements engineering, software maintenance and evolution. We first report the findings of a systematic literature review in app review mining exposing the breadth and limitations of research in this area. The thesis presents a series of contributions to address these limitations.
Research in this area has grown rapidly, resulting in a large number of scientific publications (at least 182 between 20) but nearly no independent evaluation and description of how diverse techniques fit together to support specific software engineering tasks have been performed so far. A variety of app review mining techniques have been proposed to classify reviews and to extract information such as feature requests, bug descriptions, and user sentiments but the usefulness of these techniques in practice is still unknown. Exploiting this information is however difficult due to the large number of reviews and the difficulty in extracting useful actionable information from short informal texts. App reviews -short user reviews of an app in app stores- provide a potentially rich source of information to help software development teams maintain and evolve their products. The thesis studies how mining app reviews can support software engineering.