AI Agents' Performance Optimization in Software Development
Analysis
This paper investigates how AI agents, specifically those using LLMs, address performance optimization in software development. It's important because AI is increasingly used in software engineering, and understanding how these agents handle performance is crucial for evaluating their effectiveness and improving their design. The study uses a data-driven approach, analyzing pull requests to identify performance-related topics and their impact on acceptance rates and review times. This provides empirical evidence to guide the development of more efficient and reliable AI-assisted software engineering tools.
Key Takeaways
- •AI agents actively optimize performance in software development.
- •The type of performance optimization impacts pull request outcomes.
- •Performance optimization by AI agents is more prevalent during development than maintenance.
“AI agents apply performance optimizations across diverse layers of the software stack and that the type of optimization significantly affects pull request acceptance rates and review times.”