Decision support in requirements engineering is an activity that plays an important role in enabling the delivery of value to stakeholders. Requirements prioritization has been identified as an integral (and important) part of requirements negotiation and release planning in incremental software development, which makes prioritization a key issue in requirements engineering decision support. The Analytical Hierarchy Process (AHP) has for long been considered as the technique to use when prioritizing requirements on a ratio scale. Several studies have reported positively about AHP, but lately a number of studies have also reported about weaknesses, without identifying any better ratio-scale alternatives. In this paper, the strengths and weaknesses of AHP and another ratio-scale prioritization technique, Cumulative Voting (CV), are compared. Based on this comparison, a new technique for prioritizing hierarchically structured requirements on a ratio scale is presented, called Hierarchical Cumulative Voting (HCV). HCV addresses the weaknesses of AHP while inheriting the strengths of CV. The suitability of HCV is discussed theoretically as well as in the light of empirical results from using HCV and CV in industrial settings. It is concluded that HCV seems very promising, but additional empirical studies are needed to address some of the open questions about the technique.
A Task-oriented Requirements Engineering Method for Personal Decision Support Systems - A Case Study
