Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults
📰 ArXiv cs.AI
Learn how to apply software engineering agents to diagnose Linux kernel faults and improve software quality assurance
Action Steps
- Apply LLM agents to fault localization tasks using SWE-bench benchmarks
- Configure agents to analyze Linux kernel code and identify buggy elements
- Test agent performance using metrics like accuracy and precision
- Compare agent-based fault localization with traditional methods
- Integrate agent-based FL into existing debugging workflows
Who Needs to Know This
Software engineers and developers working on Linux kernel development or maintenance can benefit from this knowledge to improve fault localization and debugging efficiency
Key Insight
💡 LLM agents can effectively diagnose Linux kernel faults, but their performance depends on configuration and testing
Share This
💡 Use LLM agents to diagnose Linux kernel faults and improve software quality!
Full Article
Title: Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults
Abstract:
arXiv:2505.19489v2 Announce Type: replace Abstract: The Linux kernel is a critical system, serving as the foundation for numerous systems. Bugs in the Linux kernel can cause serious consequences, affecting billions of users. Fault localization (FL), which aims at identifying the buggy code elements in software, plays an essential role in software quality assurance. While recent LLM agents have achieved promising accuracy in FL on recent benchmarks like SWE-bench, it remains unclear how well thes
Abstract:
arXiv:2505.19489v2 Announce Type: replace Abstract: The Linux kernel is a critical system, serving as the foundation for numerous systems. Bugs in the Linux kernel can cause serious consequences, affecting billions of users. Fault localization (FL), which aims at identifying the buggy code elements in software, plays an essential role in software quality assurance. While recent LLM agents have achieved promising accuracy in FL on recent benchmarks like SWE-bench, it remains unclear how well thes
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