David Lo

Agentic Software Issue Resolution with Large Language Models: A Survey

Software issue resolution task aims to address real-world issues in software repositories based on natural language descriptions provided by users, representing a key aspect of software maintenance. With the rapid development of large language models (LLMs) in reasoning and gener...

Learning from the Test: Self-Referential Differential Testing for Deep RL Agents

Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in real-world applications, ensuring their quality and reliability is paramount. Current works primarily focus on detecting safety-crit...

Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead

Code generation represents a critical intersection of Software Engineering (SE) and Artificial Intelligence (AI). Within this broader landscape, Verilog, as a representative hardware description language (HDL), is fundamental to Electronic Design Automation (EDA), recent research...