Review
Version 1
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The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature
Version 1
: Received: 8 March 2024 / Approved: 11 March 2024 / Online: 11 March 2024 (08:58:57 CET)
How to cite: Kokol, P. The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature. Preprints 2024, 2024030556. https://doi.org/10.20944/preprints202403.0556.v1 Kokol, P. The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature. Preprints 2024, 2024030556. https://doi.org/10.20944/preprints202403.0556.v1
Abstract
Artificial intelligence (AI) has witnessed an exponential increase in its use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems. However, a comprehensive and holistic understanding of the current status is missing. To close the above gap, synthetic knowledge synthesis was used to induce a research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and five themes, namely natural language processing in software engineering, use of artificial intelligence in the management of software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n=2042), followed by the United States (n=1193), India (n=934), Germany (n=445), and Canada (n=381). A high percentage (n=47.4%) of papers were funded, showing a strong interest in this research topic. The convergence of AI and software engineering can significantly reduce needed resources, improve quality, increase user experience, and improve the well-being of software developers.
Keywords
Software engineering; Artificial Intelligence; Machine learning; Synthetic Knowledge Synthesis
Subject
Computer Science and Mathematics, Software
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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