Citation:

Nithish Nadukuda, 2023. "Using Artificial Intelligence to Automate Front-End Development Entails Creating Intelligent Code and Trouble Shooting" ESP Journal of Engineering & Technology Advancements  3(3): 132-135.

Abstract:

Historically, manual coding and debugging have been essential components of front-end development, which is a fundamental aspect of web application development. Advancements in artificial intelligence (AI) have revolutionized the profession by offering techniques and resources to automate several aspects of earlier development. The white paper delves into the integration of artificial intelligence (AI) into front-end development workflows, with a specific focus on code generation, design optimization, and intelligent debugging. This article examines the tools and procedures that utilize artificial intelligence (AI) and emphasizes the advantages, difficulties, and potential future prospects of employing AI in front-end development.

References:

[1] GitHub Copilot. (n.d.). Retrieved from https://copilot.github.com/
[2] Adobe Sensei. (n.d.). Retrieved from https://www.adobe.com/sensei.html
[3] Vasilescu, B., Filkov, V., &Devanbu, P. (2015). "Stack Overflow and GitHub: Associations between Software Development and Crowdsourced Knowledge." In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering (ESEC/FSE), 100-112.
[4] Menzies, T., Zimmermann, T., & Nagappan, M. (2013). "Software Analytics: So What?" IEEE Software, 30(4), 32-37.
[5] Smith, J., & Johnson, A. (2023). "Automating Front-End Development with AI: From Code Generation to Intelligent Debugging." Journal of Artificial Intelligence in Software Engineering, 15(2), 112-128.
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[7] https://resources.github.com/artificial-intelligence/what-is-ai-code-generation/

Keywords:

Front-end development, Artificial Intelligence (AI), Code creation, and Design optimization. Debugging with advanced cognitive abilities, GitHub Copilot and Adobe Sensei Automatization, Artificial intelligence algorithms that can learn and improve from data, Natural language processing (NLP) User interfaces, Web development and software engineering. Algorithm bias refers to the tendency of an algorithm to systematically favor or discriminate against certain individuals or groups based on factors such as race, gender, or socioeconomic status. Issues related to the protection of personal information and the right to keep it confidential, Ethical considerations Examinations of specific instances or examples, Active participation of users, online software, Novelty.