Independent Researcher, USA.
Received on 17 August 2024; revised on 26 September 2024; accepted on 29 September 2024
As applied to software engineering, generative AI is quickly transitioning from a zero-sum industry game changer into the primary automation tool for code optimization, bug identification, and problem-solving. This technology takes advantage of artificial intelligence algorithms within machine learning models to analyze and write code, resulting in improved quality and speed of an application development process. The generative AI replenishes productivity in development work and enhances centralization between development work teams through code handling and intelligent suggestions for essential codes. However, the integration of AI in software engineering poses the following problems and ethical questions: the question of accuracy, bias, and data. This paper will review the existing knowledge on generative AI in software engineering regarding its current use, future evolutions and advancements, issues and limitations, and ethical factors in using this technology. This paper considers these aspects to give a global outlook on how generative AI will transform software development in the future and how responsible AI should be employed.
Generative AI; Software engineering; Code optimization; Bug detection; Automated debugging; Developer productivity
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Kodamasimham Krishna, Pranav Murthy and Saumya Sarangi. Exploring the synergy between generative AI and software engineering: Automating code optimization and bug fixing. World Journal of Advanced Engineering Technology and Sciences, 2024, 13(01), 682–691. Article DOI: https://doi.org/10.30574/wjaets.2024.13.1.0464