SWE-CI: Evaluating Agent Capabilities in Maintaining Codebases via Continuous Integration
📰 ArXiv cs.AI
Evaluating agent capabilities in maintaining codebases via continuous integration
Action Steps
- Propose a framework for evaluating agent capabilities in maintaining codebases
- Implement continuous integration to simulate real-world software development scenarios
- Use LLM-powered agents to automate software engineering tasks such as static bug fixing
- Analyze the performance of agents in maintaining codebases over time
Who Needs to Know This
Software engineers and DevOps teams can benefit from this research as it explores the potential of LLM-powered agents in automating software engineering tasks, particularly in maintaining codebases through continuous integration.
Key Insight
💡 LLM-powered agents can effectively maintain codebases via continuous integration, but their performance may vary depending on the complexity of requirement changes and feature iterations
Share This
💡 LLM-powered agents can automate software engineering tasks, but how well do they maintain codebases over time?
Key Takeaways
Evaluating agent capabilities in maintaining codebases via continuous integration
Full Article
Title: SWE-CI: Evaluating Agent Capabilities in Maintaining Codebases via Continuous Integration
Abstract:
arXiv:2603.03823v4 Announce Type: replace-cross Abstract: Large language model (LLM)-powered agents have demonstrated strong capabilities in automating software engineering tasks such as static bug fixing. However, in the real world, the development of mature software is typically predicated on complex requirement changes and long-term feature iterations -- a process that static, one-shot repair paradigms fail to capture. To bridge this gap, we propose SWE-CI, the first repository-level benchmar
Abstract:
arXiv:2603.03823v4 Announce Type: replace-cross Abstract: Large language model (LLM)-powered agents have demonstrated strong capabilities in automating software engineering tasks such as static bug fixing. However, in the real world, the development of mature software is typically predicated on complex requirement changes and long-term feature iterations -- a process that static, one-shot repair paradigms fail to capture. To bridge this gap, we propose SWE-CI, the first repository-level benchmar
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