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A Study on ChatGPT-Based Code Translation from Python to Java
- 1 Beijing University of Posts and Telecommunications, Beijing, 100876, China
* Author to whom correspondence should be addressed.
Abstract
Programming language translation is essential in modern software development, facilitating cross-platform compatibility and the adaptation of legacy systems. This study examines the performance of large language models (LLMs), such as ChatGPT, in Python-to-Java code translation. Using a dataset of ten diverse algorithmic problems and advanced prompt engineering techniques, we evaluate the models’ effectiveness in maintaining computational accuracy (CA) and preserving method correctness (PMC). Results indicate that LLMs perform well on standard tasks but encounter challenges in complex scenarios involving advanced data structures and recursion. These findings uncover the potential of LLMs in code translation while highlighting the need for improved prompt strategies and domain-specific fine-tuning for complex tasks.
Keywords
Large Language Models, Code Translation, Python-to-Java, Prompt Engineering, ChatGPT
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Cite this article
Gao,X. (2025). A Study on ChatGPT-Based Code Translation from Python to Java. Applied and Computational Engineering,108,26-34.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning
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