面向业务流程的需求获取和提炼的协作方法

Han Lai, Rong Peng, Y. Ni
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引用次数: 14

摘要

需求引出(RE)是系统/软件工程中的一个关键过程。它的目标是获取涉众的期望、需求和约束,这些可以被引出、分析并指定为需求。以一种自然的方式正确、清晰和完整地收集需求是一个典型的具有挑战性的问题,因为需求分析师总是在获取过程中占主导地位,而涉众则被动地参与。在本文中,我们提出了一种集体智能驱动的面向业务流程的需求获取和提炼方法。它的目的是减少需求分析师的主导地位,促进涉众的自我表达和自我完善,从而清晰而完整地引出需求。采用群体讲故事的方式促进利益相关者之间的协作和沟通,利用叙事网络模型增强故事片段之间的关联,并引入对话博弈论指导逐步提炼。同时,采用活动理论作为描述框架介绍了该方法,并给出了应用实例。最后,进行了一项先导实验,以评估其感知有用性和感知易用性;以及需求的实际质量,基于与JAD的完整性和可理解性的程度。结果表明,BPCRAR比JAD更完整、更容易理解。此外,BPCRAR在实验中表现出感知有用性和易用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A collaborative method for business process oriented requirements acquisition and refining
Requirements Elicitation (RE) is a critical process in system/software engineering. Its goal is to capture the stakeholders’ expectations, needs and constraints, which can be elicited, analyzed and specified as requirements. Gathering the requirements correctly, clearly and completely in a natural way is a typical challenging problem, because requirements analysts always play key roles in the elicitation process dominantly while stakeholders participate in passively. In this paper, we propose a collective intelligence driven business process oriented requirements acquisition and refining method. Its aim is to reduce the requirements analysts’ dominance and promote stakeholders’ self-expression and self-improvement to elicit requirements clearly and completely. It adopts the group storytelling method to promote the collaboration and communication among stakeholders, utilizes the narrative network model to enhance the associations among story fragments, and introduces dialogue game theory to guide the progressive refining. At the same time, the activity theory is adopted as the description framework to present the method and an application example is introduced. Finally, a pilot experiment is carried out to evaluate its perceived usefulness and perceived ease of use; and the actual quality of the requirements based on the degree of completeness and understandability in comparison with JAD. The results show that the requirements elicited by BPCRAR are more complete and understandable than JAD. In addition, the BPCRAR is perceived usefulness and ease of use in the experiment.
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