Improving requirements tracing via information retrieval

J. Hayes, Alex Dekhtyar, J. Osborne
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引用次数: 320

Abstract

We present an approach for improving requirements tracing based on framing it as an information retrieval (IR) problem. Specifically, we focus on improving recall and precision in order to reduce the number of missed traceability links as well as to reduce the number of irrelevant potential links that an analyst has to examine when performing requirements tracing. Several IR algorithms were adapted and implemented to address this problem. We evaluated our algorithms by comparing their results and performance to those of a senior analyst who traced manually as well as with an existing requirements tracing tool. Initial results suggest that we can retrieve a significantly higher percentage of the links than analysts, even when using existing tools, and do so in much less time while achieving comparable signal-to-noise levels.
通过信息检索改进需求跟踪
我们提出了一种改进需求跟踪的方法,该方法基于将需求跟踪定义为信息检索(IR)问题。具体地说,我们关注于提高召回率和精确度,以减少错过的可追溯性链接的数量,以及减少分析师在执行需求跟踪时必须检查的不相关的潜在链接的数量。为了解决这个问题,采用并实现了几种IR算法。我们通过将我们的算法的结果和性能与那些手动跟踪以及使用现有需求跟踪工具的高级分析师的结果和性能进行比较来评估我们的算法。初步结果表明,即使使用现有工具,我们也可以比分析人员检索到更高百分比的链接,并且在更短的时间内实现相当的信噪比水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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