Developing Tindar: A Native Arabic Programming Language

This paper introduces Tindar, a new Arabic programming language designed to ease programming education and computing interaction for Arabic speakers. Tindar features a simple, extensible structure supporting fundamental programming concepts, object-oriented programming, and functional programming features. Its architecture comprises a parser, syntactic analyzer, code generator, and virtual machine. Implemented in Rust for speed and security, the Tindar compiler outperforms Python in performance tests and is cross-platform compatible. This work emphasizes the significance of culturally and linguistically relevant computing interfaces, addressing the linguistic and technical challenges of integrating Tindar with modern development environments and offering practical solutions.

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-18
DOI
https://doi.org/10.64388/irev9i6-1712881
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing Tindar: A Native Arabic Programming Language

Iconic Research and Engineering Journals
Natural Language Processing Techniques
article

Developing Tindar: A Native Arabic Programming Language

article en

Abstract

This paper introduces Tindar, a new Arabic programming language designed to ease programming education and computing interaction for Arabic speakers. Tindar features a simple, extensible structure supporting fundamental programming concepts, object-oriented programming, and functional programming features. Its architecture comprises a parser, syntactic analyzer, code generator, and virtual machine. Implemented in Rust for speed and security, the Tindar compiler outperforms Python in performance tests and is cross-platform compatible. This work emphasizes the significance of culturally and linguistically relevant computing interfaces, addressing the linguistic and technical challenges of integrating Tindar with modern development environments and offering practical solutions.

Iconic Research and Engineering JournalsVol. 9(6)
Quality Education
Openalex Percentile: Top 19%
Natural Language Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.