30年来软件测试研究的结构与发展
Mapping the Structure and Evolution of Software Testing Research Over the Past Three Decades
摘要：
背景：软件测试领域正在快速发展。目的：根据分配给出版物的关键字，我们试图确定主要的研究主题，并了解它们是如何连接和演变的。方法：我们应用共词分析映射的拓扑结构的测试研究作为一个网络，作者指定的关键字连接的边缘，表明在出版物中的同现。关键词根据边缘密度和连接频率进行聚类。我们研究最流行的关键词，将集群总结为高级研究主题，研究主题如何连接，并研究该领域如何变化。结果：测试研究可分为16个高层次主题和18个子主题。创建指导、自动化测试生成、演化和维护以及测试预言与其他主题有着特别强的联系，突出了它们的多学科性质。新兴的关键词涉及Web和移动应用程序、机器学习、能源消耗、自动程序修复和测试生成，而新兴的连接已经在Web应用程序、测试预言机和机器学习之间形成了许多主题。随机和基于需求的测试显示潜在的下降。结论：我们的观察，建议和地图数据提供了对该领域的更深入了解，并就挑战和探索联系提供了灵感。
英文摘要：
Background: The field of software testing is growing and rapidly-evolving. Aims: Based on keywords assigned to publications, we seek to identify predominant research topics and understand how they are connected and have evolved. Method: We apply co-word analysis to map the topology of testing research as a network where author-assigned keywords are connected by edges indicating co-occurrence in publications. Keywords are clustered based on edge density and frequency of connection. We examine the most popular keywords, summarize clusters into high-level research topics, examine how topics connect, and examine how the field is changing. Results: Testing research can be divided into 16 high-level topics and 18 subtopics. Creation guidance, automated test generation, evolution and maintenance, and test oracles have particularly strong connections to other topics, highlighting their multidisciplinary nature. Emerging keywords relate to web and mobile apps, machine learning, energy consumption, automated program repair and test generation, while emerging connections have formed between web apps, test oracles, and machine learning with many topics. Random and requirements-based testing show potential decline. Conclusions: Our observations, advice, and map data offer a deeper understanding of the field and inspiration regarding challenges and connections to explore.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
