In this study, we apply co-word analysis - a text mining technique based on the co-occurrence of terms - to map the topology of software testing research topics, with the goal of providing current and prospective researchers with a map, and observations about the evolution, of the software testing field. Our analysis enables the mapping of software testing research into clusters of connected topics, from which emerge a total of 16 high-level research themes and a further 18 subthemes. This map also suggests topics that are growing in importance, including topics related to web and mobile applications and artificial intelligence. Exploration of author and country-based collaboration patterns offers similar insight into the implicit and explicit factors that influence collaboration and suggests emerging sources of collaboration for future work. We make our observations - and the underlying mapping of research topics and research collaborations - available so that researchers can gain a deeper understanding of the topology of the software testing field, inspiration regarding new areas and connections to explore, and collaborators who will broaden their perspectives.

中文翻译：

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映射软件测试中的研究主题：文献计量分析

在这项研究中，我们应用共词分析——一种基于术语共现的文本挖掘技术——来绘制软件测试研究主题的拓扑图，目的是为当前和未来的研究人员提供一个地图，以及关于软件测试领域的演变。我们的分析能够将软件测试研究映射到相关主题的集群中，从中出现总共 16 个高级研究主题和另外 18 个子主题。该地图还建议了越来越重要的主题，包括与 Web 和移动应用程序以及人工智能相关的主题。对作者和基于国家的合作模式的探索为影响合作的隐性和显性因素提供了类似的见解，并为未来工作提出了新的合作来源。