Leveraging LLMs for Automated Translation of Legacy Code: A Case Study on PL/SQL to Java Transformation

Fuente: arXiv
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Autori principali: Solovyeva, Lola, Oliveira, Eduardo Carneiro, Fan, Shiyu, Tuncay, Alper, Gareev, Shamil, Capiluppi, Andrea
Natura: Preprint
Pubblicazione: 2025
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author Solovyeva, Lola
Oliveira, Eduardo Carneiro
Fan, Shiyu
Tuncay, Alper
Gareev, Shamil
Capiluppi, Andrea
author_facet Solovyeva, Lola
Oliveira, Eduardo Carneiro
Fan, Shiyu
Tuncay, Alper
Gareev, Shamil
Capiluppi, Andrea
contents The VT legacy system, comprising approximately 2.5 million lines of PL/SQL code, lacks consistent documentation and automated tests, posing significant challenges for refactoring and modernisation. This study investigates the feasibility of leveraging large language models (LLMs) to assist in translating PL/SQL code into Java for the modernised "VTF3" system. By leveraging a dataset comprising 10 PL/SQL-to-Java code pairs and 15 Java classes, which collectively established a domain model for the translated files, multiple LLMs were evaluated. Furthermore, we propose a customized prompting strategy that integrates chain-of-guidance reasoning with $n$-shot prompting. Our findings indicate that this methodology effectively guides LLMs in generating syntactically accurate translations while also achieving functional correctness. However, the findings are limited by the small sample size of available code files and the restricted access to test cases used for validating the correctness of the generated code. Nevertheless, these findings lay the groundwork for scalable, automated solutions in modernising large legacy systems.
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id arxiv_https___arxiv_org_abs_2508_19663
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Leveraging LLMs for Automated Translation of Legacy Code: A Case Study on PL/SQL to Java Transformation
Solovyeva, Lola
Oliveira, Eduardo Carneiro
Fan, Shiyu
Tuncay, Alper
Gareev, Shamil
Capiluppi, Andrea
Software Engineering
The VT legacy system, comprising approximately 2.5 million lines of PL/SQL code, lacks consistent documentation and automated tests, posing significant challenges for refactoring and modernisation. This study investigates the feasibility of leveraging large language models (LLMs) to assist in translating PL/SQL code into Java for the modernised "VTF3" system. By leveraging a dataset comprising 10 PL/SQL-to-Java code pairs and 15 Java classes, which collectively established a domain model for the translated files, multiple LLMs were evaluated. Furthermore, we propose a customized prompting strategy that integrates chain-of-guidance reasoning with $n$-shot prompting. Our findings indicate that this methodology effectively guides LLMs in generating syntactically accurate translations while also achieving functional correctness. However, the findings are limited by the small sample size of available code files and the restricted access to test cases used for validating the correctness of the generated code. Nevertheless, these findings lay the groundwork for scalable, automated solutions in modernising large legacy systems.
title Leveraging LLMs for Automated Translation of Legacy Code: A Case Study on PL/SQL to Java Transformation
topic Software Engineering
url https://arxiv.org/abs/2508.19663