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BRIEF RESEARCH REPORT article

Front. Comput. Sci.
Sec. Software
Volume 6 - 2024 | doi: 10.3389/fcomp.2024.1473870
This article is part of the Research Topic Machine Learning for Software Engineering View all articles

Java coding using artificial intelligence

Provisionally accepted
Mafura Uandykova Mafura Uandykova 1Laura Baytenova Laura Baytenova 2Gulnar Mukhamedzhanova Gulnar Mukhamedzhanova 1*Asel Eleukulova Asel Eleukulova 3Tolkyn Mirkasimova Tolkyn Mirkasimova 1
  • 1 Narxoz University, Almaty, Kazakhstan
  • 2 Turan University, Almaty, Kazakhstan
  • 3 Kazmetengineering LLP, Almaty, Republic of Kazakhstan, Almaty, Kazakhstan

The final, formatted version of the article will be published soon.

    This study explores the potential of chatbots, specifically ChatGPT, in Java software development. The aim is to classify tasks for effective use of industrial code and develop recommendations for applying chatbot assistance, identifying boundaries where human intervention remains essential. The methodology included analyzing scientific literature and empirically testing ChatGPT-3.5 on various Java development tasks. Tasks were divided into simple (working with XML, JSON, multithreading, data input/output) and complex (writing MVC applications, REST services, GUI). Results showed that ChatGPT successfully handles simple tasks but struggles with complex problems. The study identified scenarios where the chatbot can effectively use existing codebases and design patterns to accelerate development. Conclusions highlight ChatGPT's potential in improving developer productivity, optimizing certain development tasks, and more efficiently allocating human resources in projects. However, the study also points out the need for human intervention to verify, correct, and improve generated code. The work contributes to understanding the practical usefulness of chatbots in real development scenarios and offers recommendations for integrating AI tools into the software development process.

    Keywords: Java, ChatGPT, Automated code generation, Production code, Developer Productivity

    Received: 11 Aug 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Uandykova, Baytenova, Mukhamedzhanova, Eleukulova and Mirkasimova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Gulnar Mukhamedzhanova, Narxoz University, Almaty, Kazakhstan

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.