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

摘要

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.