Will Artificial Intelligence become alternative to Software Engineers? - A Futuristic Approach
DOI:
https://doi.org/10.31305/rrijm2022.v02.n03.005Keywords:
Software Engineering, Software, Artificial Intelligence, Software EngineerAbstract
Investigating what will happen in the field of software engineering in the year 2050 is the purpose of this research. In particular, it draws attention to certain predicted best practises in the industry, the prospective roles of software engineers, and the ways in which artificial intelligence may affect the future of software engineering frameworks and the responsibilities of software engineers. In addition to this, it demonstrates the issues that are occurring right now and provides guidance on how to address them in the future. Finally, it anticipates the challenges that may arise in the future and suggests solutions to circumvent them. These forecasts were arrived at by drawing inferences about the future from existing information drawn from either the past or from current practises and ongoing research in the field of artificial intelligence software. In addition to that, a qualitative approach was used, and a survey was administered online to specialists in the fields of artificial intelligence and software engineering. As an overall outcome of this study, the replies and expectations from a variety of targeted surveys agreed that the future of the software engineering industry would undoubtedly change. On the other hand, software engineers would be the primary forces that may influence this future as well. Those who will either continue to maintain them dominating in this sector or who have been left behind and supplanted by other systems or enterprises.
References
Science Committee. NATO Software Engineering Conference, (October 1968), 231. https://doi.org/10.1093/bib/bbp050
Spector, L. (2011). Genetic Programming and Evolvable Machines: Editorial introduction. Genetic Programming and Evolvable Machines, 12(1), 1–2. https://doi.org/10.1007/s10710-010-9127-9
Wang, F., Wu, C. J., Lee, Y. C., & Yao, L. W. (2011). Regression testing of bug-fixes with AI techniques. In Advances in Intelligent and Soft Computing (Vol. 124, pp. 345–354). https://doi.org/10.1007/978-3-642-25658-5_43
Wilson, G., & Oram, A. (2007). Beautiful Code: Leading Programmers Explain How They think.O'Reilly.Sebastopol.CA