Abstract
An emerging feature of mobile application software is the need to quickly produce new versions to solve problems that emerged in previous versions. This helps adapt to changing user needs and preferences. In a continuous software development process, the user reviews collected by the apps themselves can play a crucial role to detect which components need to be reworked. This paper proposes a novel framework that enables software companies to drive their technology value stream based on the feedback (or reviews) provided by the end-users of an application. The proposed end-to-end framework exploits different Natural Language Processing (NLP) tasks to best understand the needs and goals of the end users. We also provide a thorough and in-depth analysis of the framework, the performance of each of the modules, and the overall contribution in driving the technology value stream. An analysis of reviews with sixteen popular Android Play Store applications from various genres over a long period of time provides encouraging evidence of the effectiveness of the proposed approach.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
