3 papers
cs.SE2026
Code Reasoning for Software Engineering Tasks: A Survey and A Call to Action
Saurabh Pujar, Ira Ceka, Irene Manotas +3
The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. Their performance on certain tasks can be further enhanced…
cs.SE2026
Understanding Automated Program Repair Agents Through the Lens of Traceability: An Empirical Study
Ira Ceka, Hailie Mitchell, Saurabh Pujar +5
Automated Program Repair (APR) agents leverage Large Language Models (LLMs) to autonomously diagnose and fix software bugs through reasoning, planning, and tool use. Despite impres…
cs.CR2025
Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection
Ira Ceka, Feitong Qiao, Anik Dey +3
Despite their remarkable success, large language models (LLMs) have shown limited ability on safety-critical code tasks such as vulnerability detection. Typically, static analysis…