Code-Switching Language Model

Abstract

Artificial Intelligence (AI) and Large Language Models (LLMs) have significantly transformed software development by enabling intelligent code generation, automated debugging, code translation, and natural language programming. In recent years, AI-assisted Integrated Development Environments (IDEs) have become increasingly capable of improving developer productivity; however, challenges such as limited multilingual support, fragmented development workflows, insufficient explainability, and dependence on cloud infrastructure continue to restrict their broader adoption. This survey reviews recent advances in AI-assisted programming by examining research on code generation, programming-oriented LLMs, intelligent IDEs, multilingual software development, code explanation systems, and educational AI platforms. The strengths, limitations, and emerging research trends reported in the literature are analyzed to identify existing gaps and future opportunities. Based on these findings, the survey discusses the potential of Programming Language Code Switching Language Models (CSLMs) as a promising direction for developing more intelligent, explainable, and multilingual programming environments.