1 citations · 2 across the 13 of their papers we have counts for
14 papers
LintEval: Benchmarking LLMs on Linter-Guided File Refactoring
Tongwei Deng, Jinyu Zhu, Yue Cao +3
Linters are widely used in code maintenance and real-time IDE editing to surface lint alerts related to performance, style, error-prone, and other patterns in source files. However…
FeatLens: Feature-Guided Dynamic Code Graph Construction and Retrieval for Repository-Level Code Generation
Xutian Li, Bo Xiong, Yifeng Zhu +6
Recent code generation research has moved from isolated function completion toward repository-level generation in existing codebases. To implement a target function correctly, an L…
FeatX: Editing Software by Editing Features for Repository-Level Code Evolution
Xutian Li, Yifeng Zhu, Xianlin Zhao +3
Large language models (LLMs) are increasingly used for software evolution, yet most interaction paradigms remain code-centric and require manual context management and prompt itera…
RepoSummary: Feature-Oriented Summarization and Documentation Generation for Code Repositories
Yifeng Zhu, Xianlin Zhao, Xutian Li +4
Repository summarization is a crucial research question in development and maintenance for software engineering. Existing repository summarization techniques primarily focus on sum…
Tool-integrated Reinforcement Learning for Repo Deep Search
Zexiong Ma, Chao Peng, Qunhong Zeng +3
Issue localization, the process of identifying code locations that need modification to resolve software issues, is a critical yet challenging task in software development. The sem…
Issue Retrieval and Verification Enhanced Supplementary Code Comment Generation
Yanzhen Zou, Xianlin Zhao, Xinglu Pan +1
Issue reports have been recognized to contain rich information for retrieval-augmented code comment generation. However, how to minimize hallucinations in the generated comments re…
LLMigrate: Transforming "Lazy" Large Language Models into Efficient Source Code Migrators
Yuchen Liu, Junhao Hu, Yingdi Shan +4
Rewriting C code in Rust provides stronger memory safety, yet migrating large codebases such as the 32-million-line Linux kernel remains challenging. While rule-based translators (…
SoRFT: Issue Resolving with Subtask-oriented Reinforced Fine-Tuning
Zexiong Ma, Chao Peng, Pengfei Gao +3
Mainstream issue-resolving frameworks predominantly rely on commercial models, leading to high costs and privacy concerns. Existing training approaches for issue resolving struggle…
Repository Structure-Aware Training Makes SLMs Better Issue Resolver
Zexiong Ma, Shengnan An, Zeqi Lin +2
Language models have been applied to various software development tasks, but the performance varies according to the scale of the models. Large Language Models (LLMs) outperform Sm…
Dehallucinating Parallel Context Extension for Retrieval-Augmented Generation
Zexiong Ma, Shengnan An, Zeqi Lin +3
Large language models (LLMs) are susceptible to generating hallucinated information, despite the integration of retrieval-augmented generation (RAG). Parallel context extension (PC…
Decomposing God Header File via Multi-View Graph Clustering
Yue Wang, Wenhui Chang, Tongwei Deng +2
God Header Files, just like God Classes, pose significant challenges for code comprehension and maintenance. Additionally, they increase the time required for code recompilation. H…
MESIA: Understanding and Leveraging Supplementary Nature of Method-level Comments for Automatic Comment Generation
Xinglu Pan, Chenxiao Liu, Yanzhen Zou +2
Code comments are important for developers in program comprehension. In scenarios of comprehending and reusing a method, developers expect code comments to provide supplementary in…
Comprehensive Integration of API Usage Patterns
Qi Shen, Shijun Wu, Yanzhen Zou +1
Nowadays, developers often reuse existing APIs to implement their programming tasks. A lot of API usage patterns are mined to help developers learn API usage rules. However, there…
From API to NLI: A New Interface for Library Reuse
Qi Shen, Shijun Wu, Yanzhen Zou +2
Developers frequently reuse APIs from existing libraries to implement certain functionality. However, learning APIs is difficult due to their large scale and complexity. In this pa…