A Chatbot for the Elicitation of Contextual Information from User Feedback
Paper i proceeding, 2022

Over the last years, user feedback has become a valuable source for requirements elicitation. Software vendors increasingly rely on user feedback to collect product issues and feature requests, discover requirements and monitor the overall sentiment of the users about a product. While the analysis of user feedback for requirements elicitation has revealed that feedback can contain helpful information for the product team, collecting valuable, informative, and actionable feedback is still challenging: User feedback is often vague, emotional, or missing important information, such as contextual information, to actually support a product team. Information describing the context of the reported feedback, such as the device model and software version, plays an essential role in increasing its value [1], [2]. Without a given context, reported issues can be complex to understand, reproduce, and address.

Författare

Robert Wolfinger

Universität Hamburg

Farnaz Fotrousi

Universität Hamburg

Walid Maalej

Universität Hamburg

Proceedings of the IEEE International Conference on Requirements Engineering

1090705X (ISSN) 23326441 (eISSN)

2022 IEEE 30th International Requirements Engineering Conference (RE)
Melbourne, Australia,

Ämneskategorier

Programvaruteknik

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2024-11-25