Exploiting User Feedback in Tool-Supported Multi-criteria Requirements Prioritization

As different types of user feedback are becoming available, from a variety of sources and in large amount, several analysis techniques have been developed with the purpose of extracting information that can be useful for requirements engineering purposes. For instance, automated extraction and prioritization of feature requests have been recently investigated for the specific case of app development, where the key prioritization criterion is value for the user. For other types of software applications and services, software evolution relies on multi-criteria requirements prioritization, which may take into account different stakeholders' perspectives, thus leading to a complex decision-making problem. Different automated reasoning techniques have been proposed to support multi-criteria requirements prioritization, aimed at reducing human effort and improving the quality of the resulting ranking of the candidate requirements.The goal of our research is to understand how we can exploit user feedback in tool-supported multi-criteria requirements prioritization processes. Towards this objective, we discuss the properties of user feedback which are relevant for requirements prioritization, formulate a multi-criteria requirements prioritization problem, and outline a possible solution that integrates state of the art automated reasoning techniques which we extend to cope with information derived from user feedback