7 citations · 10 across the 7 of their papers we have counts for
7 papers
IssueExec: A Test-Driven Approach for Localizing Software Engineering Issues
Jiawei Liu, Yun Lin, Chenyan Liu +5
Issue localization, which identifies code locations requiring modification from issue descriptions, is a critical step in automated software maintenance. Existing approaches predom…
Generalizing Test Cases for Comprehensive Test Scenario Coverage
Binhang Qi, Yun Lin, Xinyi Weng +4
Test cases are essential for software development and maintenance. In practice, developers derive multiple test cases from an implicit pattern based on their understanding of requi…
Learning Project-wise Subsequent Code Edits via Interleaving Neural-based Induction and Tool-based Deduction
Chenyan Liu, Yun Lin, Yuhuan Huang +5
In industrial and open-source software engineering tasks, developers often perform project-wise code editing tasks, including feature enhancement, refactoring, and bug fixing, wher…
EditFlow: Benchmarking and Optimizing Code Edit Recommendation Systems via Reconstruction of Developer Flows
Chenyan Liu, Yun Lin, Jiaxin Chang +5
Large language models (LLMs) for code editing have achieved remarkable progress, yet recent empirical studies reveal a fundamental disconnect between technical accuracy and develop…
Adaptive Confidence Gating in Multi-Agent Collaboration for Efficient and Optimized Code Generation
Haoji Zhang, Yuzhe Li, Zhenqiang Liu +3
While Large Language Models (LLMs) have catalyzed breakthroughs in automated code generation, Small Language Models (SLMs) often encounter reasoning bottlenecks and failure loops w…
Generating Project-Specific Test Cases with Requirement Validation Intention
Binhang Qi, Yun Lin, Xinyi Weng +5
Test cases are valuable assets for maintaining software quality. State-of-the-art automated test generation techniques typically focus on maximizing program branch coverage or tran…
CoEdPilot: Recommending Code Edits with Learned Prior Edit Relevance, Project-wise Awareness, and Interactive Nature
Chenyan Liu, Yufan Cai, Yun Lin +6
Recent years have seen the development of LLM-based code generation. Compared to generating code in a software project, incremental code edits are empirically observed to be more f…