Benchmarking LLaMA2 for Code Development
Evaluating AI capabilities across programming languages for scientific applications
This research evaluates LLaMA 2-70B's performance in automating software development tasks for scientific applications across multiple programming languages.
- Assesses code generation, documentation creation, and unit test development
- Measures the model's ability to translate code between programming languages
- Evaluates performance specifically in scientific computing workflows
- Provides insights into current limitations and capabilities for engineering applications
Engineering Impact: This research helps technical teams understand where LLMs can effectively augment software development processes today, particularly for scientific computing tasks, while identifying where human expertise remains essential.