This research explores how Large Language Models (LLMs) can revolutionize cross-language code clone detection, a critical challenge in modern software development.

• Demonstrates LLMs' effectiveness in identifying functional similarities across different programming languages
• Evaluates multiple LLM approaches against traditional techniques using diverse benchmarks
• Shows significant improvements in detecting semantic code clones without language-specific engineering
• Offers practical implementation strategies for integrating LLMs into existing development workflows

For engineering teams working with multiple programming languages, this research provides a scalable approach to reduce code duplication, improve maintenance, and prevent the propagation of security vulnerabilities across codebases.

Large Language Models for cross-language code clone detection