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Hierarchical Cumulative Voting (HCV) prioritization of requirements in hierarchies

机译:层次结构中需求的分层累积投票(HCV)优先级

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摘要

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 ratioscale 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.
机译:需求工程中的决策支持是一项活动,在为利益相关者提供价值方面发挥着重要作用。需求优先级已被确定为增量软件开发中需求协商和发布计划不可或缺的一部分,这使优先级成为需求工程决策支持中的关键问题。长期以来,人们一直认为分析层次结构(AHP)是在按比例确定需求优先级时要使用的技术。几项研究对AHP进行了积极的报道,但最近许多研究也对弱点进行了报道,但没有找到任何更好的比率量表替代方法。在本文中,比较了AHP的优缺点和另一种比例规模优先排序技术,即累积投票(CV)。在此比较的基础上,提出了一种新的技术,该技术用于按比例尺对层次结构化需求进行优先级排序,称为“层次累积投票”(HCV)。 HCV在继承CV优势的同时,解决了AHP的弱点。理论上以及根据工业环境中使用HCV和CV的经验结果,都讨论了HCV的适用性。结论是HCV似乎非常有前途,但是需要更多的经验研究来解决有关该技术的一些开放性问题。

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