GitTaskBench: A Benchmark for Code Agents Solving Real-World Tasks Through Code Repository Leveraging
2025-08-27
Summary
GitTaskBench is a benchmark designed to evaluate how well AI code agents can solve real-world tasks by leveraging code repositories. It includes 54 tasks across 7 domains, measuring success through execution rates and introduces an "alpha-value" metric to assess economic benefits by considering task success, token cost, and developer salaries. Experiments show that while leveraging code repositories is challenging, it remains a crucial area for improvement, with the best system solving only 48.15% of tasks.
Why This Matters
This benchmark addresses a gap in evaluating AI code agents in authentic, workflow-driven scenarios, which is crucial for the practical deployment of such agents in real-world software development. By focusing on the ability to leverage existing repositories, GitTaskBench pushes the development of code agents toward more practical, economically beneficial applications.
How You Can Use This Info
Professionals in software development and AI can use GitTaskBench to assess and improve the capabilities of AI code agents, ensuring they are economically viable and efficient in solving complex tasks. This information can guide the selection and tuning of AI models and frameworks for better performance in repository-centric environments, ultimately enhancing productivity and cost-effectiveness in software engineering projects.