Adaptive software-based Feedback Acquisition: A Persona-based design

Abstract

Users' feedback is vital to improve software quality and it provides developers with a rich knowledge on how software meets users' requirements in practice. Feedback informs how software should adapt, or be adapted, at runtime and what evolutionary actions to take in the next release. However, studies have noted that accommodating the different preferences of users on how feedback should be requested is a complex task and requires a careful engineering process. This calls for an adaptive feedback acquisition mechanisms to cater for such variability. In this paper, we tackle this problem by employing the concept of Persona to aid software engineers understand the various users' behaviours and improve their ability to design feedback acquisition techniques more efficiently. We create a set of personas based on a mixture of qualitative and quantitative studies and propose PAFA, a Persona-based method for Adaptive Feedback Acquisition.