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, and 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.

中文翻译：

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通过聚类辅助需求选择

需求选择是一个决策过程，它使项目经理能够专注于为项目结果增加最大价值的可交付成果。执行此任务是为了定义将在下一个版本中开发哪些功能或需求。这是一个复杂的多标准决策过程，许多研究工作都关注它，因为需要在商业利润和投资之间取得平衡。优先排序技术的范围从简单的定性到详细的分析优先排序方法，这些方法属于优化算法的范畴。这项工作研究了定性 MoSCoW 方法和聚类分析相结合的需求选择。我们方法的可行性已经在三个案例研究（20、50 和 100 个要求）上进行了测试。在他们每个人中，已对需求进行聚类，然后使用内部验证措施对发现的聚类配置进行了评估，以评估集群的紧凑性、连通性和可分离性。实验结果表明聚类策略用于识别软件产品的核心需求集的有效性，MoSCoW 提出的类别数量是需求优先级和协商的良好起点。