A comparative study of AI code bots: Efficiency, features, and use cases

Mihir Mehta *

Software Development Manager, Chewy.
 
Review
International Journal of Science and Research Archive, 2024, 13(01), 595–602.
Article DOI: 10.30574/ijsra.2024.13.1.1718
Publication history: 
Received on 05 August 2024; revised on 12 September 2024; accepted on 14 September 2024
 
Abstract: 
This article thus provides a comparative study of AI code bots, in terms of their performances, characteristics and applications. It looks at how via application of artificial learning and NLP for software development, these bots help in coding, debugging, and optimizing. The work also analyses AI code bots including GitHub Copilot, Tabnine, Replit Ghostwriter, Amazon CodeWhisperer, and others as well as strengths, weaknesses, and versatility of such software depending on the programming language and the development environment used. Although these tools work well in improving productivity, reducing on-task redundancies and forming a more accurate code, they do not contain self-authorization, especially for intricate occasions. The study shows that the employment of AI code bots has advantages and drawbacks that should be investigated further in the future emphasizing on the possibilities of enhancing the filters on errors, the degree of personalization and considering the ethical aspect of employing AI code generation.
 
Keywords: 
AI Code; Bots; Debugging; GitHub Copilot; Tabnine; Amazon CodeWhisperer; Chatgpt; Programming Languages
 
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0