Requirements Engineering and Software Testing are mature areas and have seen a lot of research. Nevertheless, their interactions have been sparsely explored beyond the concept of traceability. To fill this gap, we propose a definition of requirements engineering and software test (REST) alignment, a taxonomy that characterizes the methods linking the respective areas, and a process to assess alignment. The taxonomy can support researchers to identify new opportunities for investigation, as well as practitioners to compare alignment methods and evaluate alignment, or lack thereof. We constructed the REST taxonomy by analyzing alignment methods published in literature, iteratively validating the emerging dimensions. The resulting concept of an information dyad characterizes the exchange of information required for any alignment to take place. We demonstrate use of the taxonomy by applying it on five in-depth cases and illustrate angles of analysis on a set of thirteen alignment methods. In addition, we developed an assessment framework (REST-bench), applied it in an industrial assessment, and showed that it, with a low effort, can identify opportunities to improve REST alignment. Although we expect that the taxonomy can be further refined, we believe that the information dyad is a valid and useful construct to understand alignment.

翻译：需求工程和软件测试是成熟的研究领域，已涌现大量研究成果。然而，除追溯性概念外，二者交互关系的研究仍较为匮乏。为填补这一空白，我们提出了需求工程与软件测试（REST）对齐的正式定义、用于刻画两个领域间关联方法的分类体系，以及评估对齐度的流程。该分类体系既能帮助研究者发现新的研究切入点，也能支持从业者比较对齐方法并评估对齐程度（或缺失情况）。我们通过分析文献中已公开的对齐方法构建REST分类体系，并迭代验证了逐步浮现的维度。其中信息偶对（information dyad）这一核心概念，刻画了实现任何对齐所必需的信息交换机制。我们选取五组深度案例应用该分类体系，并基于十三种对齐方法展示分析维度。此外，我们还开发了评估框架REST-bench，在工业评估中验证其能以较低成本识别改进REST对齐的机会。尽管该分类体系仍有优化空间，但我们认为信息偶对是理解对齐机制的有效且实用的理论构件。