6 papers · 1 filter
SpecMind: Cognitively Inspired, Interactive Multi-Turn Framework for Postcondition Inference
Cuong Chi Le, Minh V. T Pham, Tung Vu Duy +4
Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large language model (LLM)-based methods have sh…
TestWeaver: Execution-aware, Feedback-driven Regression Testing Generation with Large Language Models
Cuong Chi Le, Cuong Duc Van, Tung Duy Vu +4
While recent advances in large language models (LLMs) have shown promise in automating test generation for regression testing, they often suffer from limited reasoning about progra…
SWE-Synth: Synthesizing Verifiable Bug-Fix Data to Enable Large Language Models in Resolving Real-World Bugs
Minh V. T. Pham, Huy N. Phan, Hoang N. Phan +3
Large language models (LLMs) are transforming automated program repair (APR) through agent-based approaches that localize bugs, generate patches, and verify fixes. However, the lac…
When Names Disappear: Revealing What LLMs Actually Understand About Code
Cuong Chi Le, Minh V. T. Pham, Cuong Duc Van +3
Large Language Models (LLMs) achieve strong results on code tasks, but how they derive program meaning remains unclear. We argue that code communicates through two channels: struct…
CodeFlow: Program Behavior Prediction with Dynamic Dependencies Learning
Cuong Chi Le, Hoang Nhat Phan, Huy Nhat Phan +2
Predicting program behavior without execution is a critical task in software engineering. Existing models often fall short in capturing the dynamic dependencies among program eleme…
RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion
Huy N. Phan, Hoang N. Phan, Tien N. Nguyen +1
Code Large Language Models (CodeLLMs) have demonstrated impressive proficiency in code completion tasks. However, they often fall short of fully understanding the extensive context…