Supporting traceability through affinity mining

V. Gervasi, D. Zowghi
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引用次数: 29

Abstract

Traceability among requirements artifacts (and beyond, in certain cases all the way to actual implementation) has long been identified as a critical challenge in industrial practice. Manually establishing and maintaining such traces is a high-skill, labour-intensive job. It is often the case that the ideal person for the job also has other, highly critical tasks to take care of, so offering semi-automated support for the management of traces is an effective way of improving the efficiency of the whole development process. In this paper, we present a technique to exploit the information contained in previously defined traces, in order to facilitate the creation and ongoing maintenance of traces, as the requirements evolve. A case study on a reference dataset is employed to measure the effectiveness of the technique, compared to other proposals from the literature.
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通过关联挖掘支持可追溯性
需求工件之间的可追溯性(在某些情况下,一直到实际实现)长期以来一直被认为是工业实践中的一个关键挑战。手动建立和维护这些痕迹是一项高技能、劳动密集型的工作。通常情况下,理想的工作人员也有其他非常重要的任务要处理,因此为跟踪管理提供半自动化的支持是提高整个开发过程效率的有效方法。在本文中,我们提出了一种技术来利用先前定义的轨迹中包含的信息,以便随着需求的发展促进轨迹的创建和持续维护。通过对参考数据集的案例研究来衡量该技术的有效性,并与文献中的其他建议进行比较。
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