Mapping Research Topics in Software Testing: A Bibliometric Analysis
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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 keywords are connected by edges indicating co-occurrence in publications. Nodes are clustered based on edge density and strength. We examine the most popular keywords, summarize clusters into research topics, examine how clusters connect, and identify emerging and declining keywords, topics, and edges. Results: Testing research can be divided into 16 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 applications, machine learning, energy consumption, automated program repair and test generation, while emerging connections have formed between web applications, 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.
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