  Requirements selection is a decision-making process that enables project
managers to focus on the deliverables that add most value to the project
outcome. This task is performed to define which features or requirements will
be developed in the next release. It is a complex multi-criteria decision
process that has been focused by many research works because a balance between
business profits and investment is needed. The spectrum of prioritization
techniques spans from simple and qualitative to elaborated analytic
prioritization approaches that fall into the category of optimization
algorithms. This work studies the combination of the qualitative MoSCoW method
and cluster analysis for requirements selection. The feasibility of our
methodology has been tested on three case studies (with 20, 50 and 100
requirements). In each of them, the requirements have been clustered, then the
clustering configurations found have been evaluated using internal validation
measures for the compactness, connectivity and separability of the clusters.
The experimental results show the validity of clustering strategies for the
identification of the core set of requirements for the software product, being
the number of categories proposed by MoSCoW a good starting point in
requirements prioritization and negotiation.
