3 papers
cs.SE2026
How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repair
Ramtin Ehsani, Irene Manotas, Saurabh Pujar +2
Large Language Model (LLM)-based Automated Program Repair systems are advancing rapidly, yet their performance remains inconsistent. Even when provided with the same contextual inf…
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
Automated Customization of LLMs for Enterprise Code Repositories Using Semantic Scopes
Ulrich Finkler, Irene Manotas, Wei Zhang +3
Code completion (CC) is a task frequently used by developers when working in collaboration with LLM-based programming assistants. Despite the increased performance of LLMs on publi…