Artificial intelligence applied to software testing. A tertiary study

Context: Artificial intelligence (AI) methods and models have extensively been applied to support different phases of the software development lifecycle, including software testing (ST). Several secondary studies investigated the interplay between AI and ST but restricted the scope of the research to specific domains or sub-domains within either area. Objective: This research aims to explore the overall contribution of AI to ST, while identifying the most popular applications and potential paths for future research directions. Method: We executed a tertiary study following well-established guidelines for conducting systematic literature mappings in software engineering and for answering nine research questions. Results: We identified and analyzed 20 relevant secondary studies. The analysis was performed by drawing from well-recognized AI and ST taxonomies and mapping the selected studies according to them. The resulting mapping and discussions provide extensive and detailed information on the interplay between AI and ST. Conclusion: The application of AI to support ST is a well-consolidated and growing interest research topic. The mapping resulting from our study can be used by researchers to identify opportunities for future research, and by practitioners looking for evidence-based information on which AI-supported technology to possibly adopt in their testing processes.