Home // International Journal On Advances in Intelligent Systems, volume 12, numbers 1 and 2, 2019 // View article
Authors:
Matthias Jurisch
Stephan Böhm
Maria Lusky
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 two approaches based on textual similarity of user stories for a recommendation system: the first approach uses standard information retrieval techniques whereas the second approach uses a more recent approach from language modeling, namely word embeddings. We also present a three-step evaluation of these approaches, comprising of a data analysis, a survey and a user study. The results tend to support the information retrieval approach and not only show that user story similarity rated by users and rated by such an algorithm is connected, but also demonstrate a strong relation between user story similarity and their usefulness for inter-project knowledge transfer. Besides, our evaluation shows that using word embeddings showed worse results than the established information retrieval approach in the domain of large enterprise application development.
Pages: 60 to 69
Copyright: Copyright (c) to authors, 2019. Used with permission.
Publication date: June 30, 2019
Published in: journal
ISSN: 1942-2679