This research evaluates how Large Language Models perform when generating code for specific domains like web development, gaming, and mathematics.

• LLMs trained on broad datasets show limitations when handling domain-specific programming challenges
• Traditional benchmarks like HumanEval fail to capture the complexities of specialized programming environments
• The study establishes a framework for assessing LLM capabilities in professional software development contexts
• Results highlight the gap between general coding capability and domain expertise in LLMs

For engineering teams, this research provides critical insights on when to rely on LLMs for specialized development tasks and where human expertise remains essential.

On the Effectiveness of Large Language Models in Domain-Specific Code Generation