A method for prioritizing end-user feedback for requirements engineering

Today´s software-intensive systems exhibit an increasing complexity due to a broad spectrum of technical and sociotechnical aspects leading to rapid changes in requirements. To monitor these changes, we developed the ConTexter feedback system that enables end-user feedback submitted as narrative text enriched with multimedia attachments. Analyzing received end-user feedback is a work-intensive task. Thus, problems and changes in end-users´ needs reach responsible requirements engineers after a significant delay. Automatic techniques are required to support this tasks. In this paper, we investigate whether end-user feedback can be prioritized automatically by combining keyword-based information retrieval and descriptive statistics. Moreover, we show in an evaluation that the obtained results are reasonable.