Abstract
Feedback about software applications and services that end-users express through web-based communication platforms represents an invaluable knowledge source for diverse software engineering tasks, including requirements elicitation. Research work on automated analysis of textual messages in app store reviews, open source software (OSS) mailing-lists and user forums has been rapidly increasing in the last five years. NLP techniques are applied to filter out irrelevant data, text mining and automated classification techniques are then used to classify messages into different categories, such as bug report and feature request. Our research focuses on online discussions that take place in user forums and OSS mailing-lists, and aims at providing automated analysis techniques to discover contained requirements. In this paper, we present a speech-acts based analysis technique, and experimentally evaluate it on a dataset taken from a widely used OSS project.
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.
