ǂThe ǂuse of AI in software engineering

ǂa ǂsynthetic knowledge synthesis of the recent research literature

Abstract

Artificial intelligence (AI) has witnessed an exponential increase in 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 needs to be included. To close the above gap, synthetic knowledge synthesis was used to induce the research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and 5 themes—namely, natural language processing in software engineering, use of artificial intelligence in the management of the 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 the strong interest in this research topic. The convergence of AI and software engineering can significantly reduce the required resources, improve the quality, enhance the user experience, and improve the well-being of software developers.

Keywords

software engineering;artificial intelligence;machine learning;synthetic knowledge synthesis;AI;

Data

Language:	English
Year of publishing:	2024
Typology:	1.02 - Review Article
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	MDPI
UDC:	004.8
COBISS:	199165187
ISSN:	2078-2489
Views:	0
Downloads:	6
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	umetna inteligenca;strojno učenje;sinteza znanja;
Type (COBISS):	Article
Pages:	14 str.
Volume:	ǂVol. ǂ15
Issue:	ǂiss. ǂ6, [art. no.] 354
Chronology:	2024
DOI:	10.3390/info15060354
ID:	26914722