article · International Journal for Research in Applied Science and Engineering Technology · 2023
AI Pair Programming Tool
Cited by 0Open access
Abstract
Abstract: In the ever-evolving landscape of software development, the need for tools that augment developer productivity is paramount. This paper introduces a novel integration of IntelliJ IDEA, a widely used integrated development environment (IDE), with OpenAI's advanced deep learning models. The synergy between these two technologies aims to elevate the coding experience by providing intelligent code assistance, allowing developers to write code more efficiently and with greater accuracy. Our approach leverages OpenAI's natural language processing capabilities to enhance code suggestions, auto-completions, and error detection within IntelliJ IDEA. By analyzing vast code repositories and learning from diverse coding patterns, our system empowers developers with context-aware recommendations, significantly reducing the cognitive load associated with code creation. This paper presents the architecture of our solution, detailing the seamless integration of OpenAI's models into the IntelliJ IDEA IDE. We discuss the methodology behind training the models, emphasizing their adaptability to various programming languages and project structures. Furthermore, we present empirical results demonstrating the effectiveness of our approach in real-world coding scenarios.
Cite this paper
Magar, P. A. (2023). AI Pair Programming Tool. International Journal for Research in Applied Science and Engineering Technology, 11(11), 1963–1967. https://doi.org/10.22214/ijraset.2023.56723
Magar, Prof. Anand. “AI Pair Programming Tool.” International Journal for Research in Applied Science and Engineering Technology, vol. 11, no. 11, 2023, pp. 1963–67, https://doi.org/10.22214/ijraset.2023.56723.
Magar, Prof. Anand. 2023. “AI Pair Programming Tool.” International Journal for Research in Applied Science and Engineering Technology 11 (11): 1963–67. https://doi.org/10.22214/ijraset.2023.56723.
Magar, P.A. (2023) ‘AI Pair Programming Tool’, International Journal for Research in Applied Science and Engineering Technology, 11(11), pp. 1963–1967. Available at: https://doi.org/10.22214/ijraset.2023.56723.
@article{magar2023pair,
title = {{AI Pair Programming Tool}},
author = {Magar, Prof. Anand},
journal = {International Journal for Research in Applied Science and Engineering Technology},
volume = {11},
number = {11},
pages = {1963--1967},
year = {2023},
doi = {10.22214/ijraset.2023.56723}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.