It is well recognized that traceability links between software artifacts provide crucial support in comprehension, efficient development, and effective management of a software system. However, automated traceability systems to date have been faced with two major open research challenges: how to extract traceability links with both high precision and high recall, and how to efficiently visualize links for complex systems because of scalability and visual clutter issues. To overcome the two challenges, we designed and developed a traceability system, DCTracVis. This system employs an approach that combines three supporting techniques, regular expressions, key phrases, and clustering, with information retrieval (IR) models to improve the performance of automated traceability recovery between documents and source code. This combination approach takes advantage of the strengths of the three techniques to ameliorate limitations of IR models. Our experimental results show that our approach improves the performance of IR models, increases the precision of retrieved links, and recovers more correct links than IR alone. After having retrieved high-quality traceability links, DCTracVis then utilizes a new approach that combines treemap and hierarchical tree techniques to reduce visual clutter and to allow the visualization of the global structure of traces and a detailed overview of each trace, while still being highly scalable and interactive. Usability evaluation results show that our approach can effectively and efficiently help software developers comprehend, browse, and maintain large numbers of links.

中文翻译：

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DCTracVis：检索和可视化源代码和文档之间的可追溯性链接的系统

众所周知，软件工件之间的可追溯性链接为软件系统的理解、高效开发和有效管理提供了关键支持。然而，迄今为止，自动化溯源系统面临着两个主要的开放研究挑战：如何提取具有高精度和高召回率的溯源链接，以及由于可扩展性和视觉混乱问题，如何有效地可视化复杂系统的链接。为了克服这两个挑战，我们设计并开发了一个可追溯系统 DCTracVis。该系统采用了一种将正则表达式、关键短语和聚类三种支持技术与信息检索 (IR) 模型相结合的方法，以提高文档和源代码之间自动追溯恢复的性能。这种组合方法利用了三种技术的优势来改善 IR 模型的局限性。我们的实验结果表明，与单独使用 IR 相比，我们的方法提高了 IR 模型的性能，提高了检索链接的精度，并恢复了更多正确的链接。在检索到高质量的可追溯性链接后，DCTracVis 然后利用一种结合树图和分层树技术的新方法来减少视觉混乱并允许轨迹的全局结构和每个轨迹的详细概述的可视化，同时仍然具有高度的可扩展性和互动。可用性评估结果表明，我们的方法可以有效且高效地帮助软件开发人员理解、浏览和维护大量链接。