Holistic data-driven requirements elicitation in the big data era

被引:6
|
作者
Henriksson, Aron [1 ]
Zdravkovic, Jelena [1 ]
机构
[1] Stockholm Univ, Dept Comp & Syst Sci, POB 7003, S-16407 Kista, Sweden
来源
SOFTWARE AND SYSTEMS MODELING | 2022年 / 21卷 / 04期
关键词
Data-driven requirements engineering; Big data; Requirements modeling; Machine learning; Natural language processing;
D O I
10.1007/s10270-021-00926-6
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Digital transformation stimulates continuous generation of large amounts of digital data, both in organizations and in society at large. As a consequence, there have been growing efforts in the Requirements Engineering community to consider digital data as sources for requirements acquisition, in addition to human stakeholders. The volume, velocity and variety of the data make requirements discovery increasingly dynamic, but also unstructured and complex, which current elicitation methods are unable to consider and manage in a systematic and efficient manner. We propose a framework, in the form of a conceptual metamodel and a method, for continuous and automated acquisition, analysis and aggregation of heterogeneous digital sources that aims to support data-driven requirements elicitation and management. The usability of the framework is partially validated by an in-depth case study from the business sector of video game development.
引用
收藏
页码:1389 / 1410
页数:22
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