7 citations · 8 across the 3 of their papers we have counts for
5 papers · 1 filter
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…
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…
RepoMasterEval: Evaluating Code Completion via Real-World Repositories
Qinyun Wu, Chao Peng, Pengfei Gao +9
With the growing reliance on automated code completion tools in software development, the need for comprehensive evaluation benchmarks has become critical. Existing benchmarks focu…
VersiCode: Towards Version-controllable Code Generation
Tongtong Wu, Weigang Wu, Xingyu Wang +7
Large Language Models (LLMs) have made tremendous strides in code generation, but existing research fails to account for the dynamic nature of software development, marked by frequ…