The system was evaluated on real-world tasks such as API migration and temporal code edits, demonstrating its ability to identify more correct code blocks to modify and produce valid final code repositories without build issues. Despite some limitations, such as reliance on static analysis and the need for more extensive testing, the researchers believe that CodePlan has the potential to significantly improve developer productivity and software quality. Future work will focus on expanding the framework to more languages and software projects, enhancing the dependency graph, and exploring ways to edit multiple related code blocks in parallel.
Key takeaways:
- CodePlan is a new system proposed by Microsoft researchers that automates complex repository-level coding tasks using AI and natural language processing.
- CodePlan works by decomposing the overall repository task into incremental steps, guided by a large language model's localization strength but augmented with rigorous planning and analysis.
- The system was evaluated on real-world tasks and demonstrated its strengths by identifying more correct code blocks to modify compared to baselines and producing valid final code repositories without build issues.
- While CodePlan has some limitations, such as relying on static analysis and focusing on editing one code block at a time, it offers a promising path to expand AI's advantages into complex 'outer loop' development challenges.