Open innovation in software requirements engineering: A mapping study

Huishi Yin, Dietmar Pfahl
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引用次数: 2

Abstract

Background: Since 2003, when the concept of open innovation (OI) was introduced, OI has been applied in many industrial fields. Previous research indicates that the use of OI in computer science is less diverse than in other fields. Especially, the role of OI in software requirements engineering (RE) seems to be little explored. Goals: This study aimed to summarize the body of knowledge about the use of OI in the field of RE. More specifically, we analyzed what uses of OI in the context of RE have been reported and how OI has contributed to individual steps of the RE process. Method: We conduct a mapping study on the literature provided in four scientific databases (ISI Web of Science, IEEE Xplore, ACM Digital Library, and Science Direct). Results: We identified 20 relevant papers. We found: 1) 20 primary studies from the period 2003–2016 report on results about applying OI in RE. 2) Half of the studies report on the application of OI on RE as a whole. 3) Only one paper each is related to requirement prioritization and validation. 4) None of the primary studies presents a proprietary tool support for OI in RE. Only one study presents a method for automatic requirements extraction in OSS projects which can be implemented using standard machine learning tools. Conclusions: Acknowledging the lack of published research on the use of OI strategies in specific RE activities, i.e., prioritization and validation, as well as the lack of reported tool support, we see new opportunities for research on automated and thus non-intrusive and low-cost methods for applying OI strategies in RE.
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软件需求工程中的开放式创新:映射研究
背景:自2003年开放式创新(open innovation, OI)概念被提出以来,开放式创新在许多工业领域得到了应用。先前的研究表明,计算机科学中OI的使用不如其他领域多样化。特别是,OI在软件需求工程(RE)中的作用似乎很少被探索。目的:本研究旨在总结有关成骨不全在可再生医学领域应用的知识体系。更具体地说,我们分析了在可再生医学背景下的成骨不全有哪些应用,以及成骨不全如何促进可再生医学过程的各个步骤。方法:我们对四个科学数据库(ISI Web of Science、IEEE Xplore、ACM Digital Library和Science Direct)提供的文献进行制图研究。结果:检索到相关文献20篇。我们发现:1)2003-2016年期间关于在RE中应用OI的结果报告的20项主要研究。2)一半的研究报告了OI在RE中的整体应用。3)只有一篇论文与需求优先级和验证相关。4)没有一项主要的研究提出了在可再生能源中支持OI的专有工具。只有一项研究提出了在OSS项目中自动提取需求的方法,该方法可以使用标准的机器学习工具来实现。结论:承认缺乏关于在特定的RE活动中使用OI策略的公开研究,即优先级和验证,以及缺乏报告的工具支持,我们看到了在RE中应用OI策略的自动化、非侵入性和低成本方法研究的新机会。
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