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cloud.google.com·7h ago
AI Research
arXiv CS.AI·Aug 24·5 min read
Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agenda
TL;DR
Large Language Models (LLMs) are evolving from simple code completion tools to sophisticated agents capable of managing software repositories and security workflows. This survey identifies key challenges and proposes a research agenda focused on integrating functional and security evaluations for LLMs.
✦ Why It Matters
Focus on developing LLMs that integrate security and functionality to enhance software reliability today.
Key Takeaways
- Integrate security evaluations into LLM development processes.
- Adopt the proposed minimum reporting protocol for better comparisons.
- Prioritize benchmarks that assess both functionality and security.
- Implement calibrated human oversight in LLM workflows.
How It Works
The assurance framework introduced in the survey categorizes LLM evaluations into functional correctness, security, operational reliability, evidence provenance, and agent authority. This structured approach helps in assessing the capabilities of LLMs beyond mere performance metrics.