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通过基于上下文历史的推荐实现无处不在的需求工程。

Towards ubiquitous requirements engineering through recommendations based on context histories.

作者信息

Lima Robson, Filippetto Alexsandro S, Heckler Wesllei, Barbosa Jorge L V, Leithardt Valderi R Q

机构信息

Applied Computing Graduate Program (PPGCA), University of Vale do Rio dos Sinos (UNISINOS), São Leopoldo, RS, Brazil.

VALORIZA-Research Centre for Endogenous Resource Valorization, Polytechnic Institute of Portalegre, Portalegre, Portugal.

出版信息

PeerJ Comput Sci. 2022 Jan 3;8:e794. doi: 10.7717/peerj-cs.794. eCollection 2022.

Abstract

The growing technological advance is causing constant business changes. The continual uncertainties in project management make requirements engineering essential to ensure the success of projects. The usual exponential increase of stakeholders throughout the project suggests the application of intelligent tools to assist requirements engineers. Therefore, this article proposes Nhatos, a computational model for ubiquitous requirements management that analyses context histories of projects to recommend reusable requirements. The scientific contribution of this study is the use of the similarity analysis of projects through their context histories to generate the requirement recommendations. The implementation of a prototype allowed to evaluate the proposal through a case study based on real scenarios from the industry. One hundred fifty-three software projects from a large bank institution generated context histories used in the recommendations. The experiment demonstrated that the model achieved more than 70% stakeholder acceptance of the recommendations.

摘要

不断发展的技术进步正在引发持续的业务变革。项目管理中持续存在的不确定性使得需求工程对于确保项目成功至关重要。在整个项目中,利益相关者通常呈指数级增长,这表明需要应用智能工具来协助需求工程师。因此,本文提出了Nhatos,这是一种用于普适需求管理的计算模型,它通过分析项目的上下文历史来推荐可复用的需求。本研究的科学贡献在于通过项目的上下文历史进行相似性分析以生成需求推荐。通过一个基于行业实际场景的案例研究对原型进行实施,从而对该提议进行评估。一家大型银行机构的153个软件项目生成了用于推荐的上下文历史。实验表明,该模型实现了超过70%的利益相关者对推荐的接受度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b93/8771779/76eaf2d2e1dd/peerj-cs-08-794-g001.jpg

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