探索需求知识激发架构思维

Preethu Rose Anish, Balaji Balasubramaniam, A. Sainani, J. Cleland-Huang, M. Daneva, R. Wieringa, S. Ghaisas
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引用次数: 14

摘要

软件需求规范(sss)通常缺乏做出明智的体系结构决策所需的细节。因此,架构师要么做出可能导致错误决策的假设,要么进行额外的涉众访谈,从而导致潜在的项目延迟。我们之前观察到,软件架构师会询问试探性问题(PQs)来收集对架构决策至关重要的信息。我们的目标是为业务分析师提供适当的pq,以便他们能够自己提出这些问题。我们报告了一项由40多位经验丰富的架构师参与的新研究,以确定五个功能领域的可重用pq,并将它们组织到结构化流中。业务分析人员可以使用这些pqflow来引出和指定与体系结构相关的信息。此外,我们利用机器学习技术来确定pq流何时适合在项目中使用,并使用从现有SRS中提取的相关信息注释单个pq。我们对114个需求规范中的8000多个单独需求进行了培训和评估,并进行了试点研究以验证其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probing for Requirements Knowledge to Stimulate Architectural Thinking
Software requirements specifications (SRSs) often lack the detail needed to make informed architectural decisions. Architects therefore either make assumptions, which can lead to incorrect decisions, or conduct additional stakeholder interviews, resulting in potential project delays. We previously observed that software architects ask Probing Questions (PQs) to gather information crucial to architectural decision-making. Our goal is to equip Business Analysts with appropriate PQs so that they can ask these questions themselves. We report a new study with over 40 experienced architects to identify reusable PQs for five areas of functionality and organize them into structured flows. These PQflows can be used by Business Analysts to elicit and specify architecturally relevant information. Additionally, we leverage machine learning techniques to determine when a PQ-flow is appropriate for use in a project, and to annotate individual PQs with relevant information extracted from the existing SRS. We trained and evaluated our approach on over 8,000 individual requirements from 114 requirements specifications and also conducted a pilot study to validate its usefulness.
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