Home // CENTRIC 2018, The Eleventh International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services // View article


Evaluating a User Story Based Recommendation System for Supporting Development Processes in Large Enterprise

Authors:
Maria Lusky
Matthias Jurisch
Stephan Böhm
Katharina Kahlcke

Keywords: Mobile Enterprise Applications; User Stories; Recommendation Systems; User Centered Design.

Abstract:
In mobile application development projects, large enterprises have to face special challenges. To meet these challenges and to meet today’s high expectations on user centered design, inter-project knowledge transfer of software artifacts becomes an important aspect for large software development companies. For supporting this kind of knowledge transfer, we propose an approach for a recommendation system based on textual similarity of user stories that are computed via standard information retrieval techniques. We also present a three-step evaluation of this approach, comprising data analysis, a survey and a user study. The results tend to support our approach and not only show that user story similarity rated by users and rated by an algorithm correlates, but also demonstrate a strong relation between user story similarity and their usefulness for inter-project knowledge transfer.

Pages: 18 to 23

Copyright: Copyright (c) IARIA, 2018

Publication date: October 14, 2018

Published in: conference

ISSN: 2308-3492

ISBN: 978-1-61208-670-5

Location: Nice, France

Dates: from October 14, 2018 to October 18, 2018