Home // International Journal On Advances in Intelligent Systems, volume 10, numbers 1 and 2, 2017 // View article

Evaluating a Recommendation System for User Stories in Mobile Enterprise Application Development

Authors:
Matthias Jurisch
Maria Lusky
Bodo Igler
Stephan Böhm

Keywords: Mobile Enterprise Applications; User Stories; Recommendation Systems; Pattern Inventories

Abstract:
Mobile application development is characterized by a higher market volatility and shorter development cycles than traditional desktop application development. Developing mobile applications in large enterprise contexts (mobile enterprise applications) requires additional effort to adapt to new circumstances, since complex processes, user roles and enterprisespecific guidelines need to be taken into account. This effort can be reduced by reusing artifacts from other projects, such as source code, wireframes, documentation, screen designs or requirement specifications. We propose a recommendation system based on user stories in order to make artifacts accessible without requiring users to formulate an explicit search query. We present a prototype implementing this approach using standard methods and tools from information retrieval and evaluate it using different components of user stories as well as taking into account varying user story quality. The results show that using only user story text for calculating recommendations is the most promising approach and that user story quality does not affect the efficiency of recommendations.

Pages: 40 to 47

Copyright: Copyright (c) to authors, 2017. Used with permission.

Publication date: June 30, 2017

Published in: journal

ISSN: 1942-2679