Lightweight Software Language Processing Using Antlr and CGTL

Kevin Lano, Qiaomu Xue

2023

Abstract

Software complexity has become a significant social problem, which MDE endeavours to alleviate, however MDE approaches and tools often introduce additional complexity which prevents general software practitioners from benefiting from MDE solutions. In this paper we present an alternative approach for MDE in the domain of language processing, using lightweight tools (Antlr and CGTL) suitable for general industrial use. We evaluate the approach on tasks of DSL definition, software abstraction, and program translation, based on our experience with industrial applications of MDE.

Paper Citation

in Harvard Style

Lano K. and Xue Q. (2023). Lightweight Software Language Processing Using Antlr and CGTL. In Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD, ISBN 978-989-758-633-0, pages 19-30. DOI: 10.5220/0011623000003402

in Bibtex Style

@conference{modelsward23,
author={Kevin Lano and Qiaomu Xue},
title={Lightweight Software Language Processing Using Antlr and CGTL},
booktitle={Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD,},
year={2023},
pages={19-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011623000003402},
isbn={978-989-758-633-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD,
TI - Lightweight Software Language Processing Using Antlr and CGTL
SN - 978-989-758-633-0
AU - Lano K.
AU - Xue Q.
PY - 2023
SP - 19
EP - 30
DO - 10.5220/0011623000003402