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Analysing Software Quality of AI-Translated Code: A Comparative Study of Large Language Models Using Static Analysis Cover

Analysing Software Quality of AI-Translated Code: A Comparative Study of Large Language Models Using Static Analysis

Applied Computer Systems
Volume 30 (2025): Issue 1 (January 2025)
By: Vikram Bhutani,  Farshad Ghassemi Toosi and  Jim Buckley  
Open Access
|Oct 2025

Authors

Vikram Bhutani

vikram.bhutani@intel.com

Computer Science Department, Munster Technological University, Cork, Ireland

Farshad Ghassemi Toosi

farshad.toosi@mtu.ie

Computer Science Department, Munster Technological University, Cork, Ireland

Jim Buckley

Jim.Buckley@ul.ie

Computer Science Department, University of Limerick, Limerick, Ireland
DOI: https://doi.org/10.2478/acss-2025-0013 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 105 - 121
Submitted on: Jul 19, 2025
Accepted on: Oct 3, 2025
Published on: Oct 23, 2025
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Artificial intelligence,
ChatGPT4.1,
C++,
deep learning,
DeepSeek R1,
Java,
machine learning,
NMT,
object oriented,
programming languages translation,
Python,
source code translation,
SMT
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2025 Vikram Bhutani, Farshad Ghassemi Toosi, Jim Buckley, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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