Using Data Mining and Recommender Systems to Scale Up the Requirements Process
Ultra-Large-Scale (ULS) software systems' projects are anticipated to be highly complex and to involve thousands, or even hundreds of thousands of stakeholders. Unfortunately numerous accounts of recent failures and challenges in industrial and governmental projects have demonstrated that current requirements elicitation and prioritization practices do not scale adequately to address the needs of large projects. This position paper directly addresses this problem through proposing an open, inclusive, and robust elicitation and prioritization process that utilizes data-mining and recommender technologies to facilitate the active involvement of many thousands of stakeholders. The paper believes that the approach described in this paper is a fundamental building block towards addressing higher level requirements problems facing ULS Systems.