*Result*: Using LLMs to Extract OCL Specifications from Java and Python Programs:An Empirical Study
Title:
Using LLMs to Extract OCL Specifications from Java and Python Programs:An Empirical Study
Authors:
Source:
Siala, H & Lano, K 2025, 'Using LLMs to Extract OCL Specifications from Java and Python Programs : An Empirical Study', CEUR Workshop Proceedings, vol. 4122.
Publication Year:
2025
Collection:
King's College, London: Research Portal
Subject Terms:
Document Type:
*Academic Journal*
article in journal/newspaper
File Description:
application/pdf
Language:
English
Availability:
Rights:
info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
Accession Number:
edsbas.B08DF974
Database:
BASE
*Further Information*
*This paper presents a comprehensive study of the application of several open-source Large Language Models (LLMs) for abstracting Object Constraint Language (OCL) specifications from source code. We aim to provide researchers and developers with insights into the capabilities and limitations of using different LLMs to abstract OCL specifications from code. We evaluate a collection of open-source LLMs of comparable size (StarCoder2, LLaMA, CodeLlama, Mistral, and DeepSeek) by prompting them to generate OCL specifications for both Java and Python programs. The results show that both Mistral and DeepSeek outperform other LLMs in abstracting OCL specifications from both languages.*