SAFFRON: A Semi-Automated Framework for Software Requirements Prioritization
This addresses the cost of frequent re-prioritization in agile software development for stakeholders and developers, though it is incremental as it builds on existing collaborative filtering methods.
The paper tackles the rank reversal problem in software requirements prioritization by introducing SAFFRON, a semi-automated framework that predicts stakeholder ratings to reduce human interactions, achieving a 13.5-27% reduction in such interactions.
Due to dynamic nature of current software development methods, changes in requirements are embraced and given proper consideration. However, this triggers the rank reversal problem which involves re-prioritizing requirements based on stakeholders' feedback. It incurs significant cost because of time elapsed in large number of human interactions. To solve this issue, a Semi-Automated Framework for soFtware Requirements priOritizatioN (SAFFRON) is presented in this paper. For a particular requirement, SAFFRON predicts appropriate stakeholders' ratings to reduce human interactions. Initially, item-item collaborative filtering is utilized to estimate similarity between new and previously elicited requirements. Using this similarity, stakeholders who are most likely to rate requirements are determined. Afterwards, collaborative filtering based on latent factor model is used to predict ratings of those stakeholders. The proposed approach is implemented and tested on RALIC dataset. The results illustrate consistent correlation, similar to state of the art approaches, with the ground truth. In addition, SAFFRON requires 13.5-27% less human interaction for re-prioritizing requirements.