3 citations · 11 across the 21 of their papers we have counts for
19 papers
Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation
Kefeng Duan, Dewu Zheng, Yanlin Wang +8
The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repository context. Since real-worl…
From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Bench
Dewu Zheng, Yanlin Wang, Xiwen Wang +5
In real-world software development, code review typically involves iterative interactions between developers and reviewers to improve software quality, making the process costly an…
RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models
Yanlin Wang, Suiquan Wang, Yanli Wang +4
Recent large language models (LLMs) have shown strong performance on software engineering tasks, yet most existing benchmarks evaluate code reasoning at the function level, where a…
PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents
Tianyue Jiang, Yanlin Wang, Xin He +7
While Large Language Models have greatly advanced automated issue resolution, existing agent-based methods exhibit a fundamental limitation in their insufficient exploration of rep…
Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code
Kaifeng He, Xiaojun Zhang, Peiliang Cai +7
Large language models (LLMs) frequently generate defective code, ranging from logical bugs to security vulnerabilities. Training-data quality is one contributor to these outcomes a…
AnomalyGen: Enhancing Log-Based Anomaly Detection with Code-Guided Data Augmentation
Xinyu Li, Yintong Huo, Chenxi Mao +4
Log-based anomaly detection is fundamentally constrained by training data sparsity. Our empirical study reveals that public benchmark datasets cover less than 10% of source code lo…
Architecture-Aware Multi-Design Generation for Repository-Level Feature Addition
Mingwei Liu, Zhenxi Chen, Zheng Pei +3
Implementing new features across an entire codebase presents a formidable challenge for Large Language Models (LLMs). This proactive task requires a deep understanding of the globa…
His2Trans: A Knowledge-Guided Agentic Framework for Project-Level C-to-Rust Migration
Shengbo Wang, Mingwei Liu, Guangsheng Ou +3
C remains a major implementation language for operating systems, embedded platforms, and infrastructure software, but manual memory management continues to create security and main…
DRAINCODE: Stealthy Energy Consumption Attacks on Retrieval-Augmented Code Generation via Context Poisoning
Yanlin Wang, Jiadong Wu, Tianyue Jiang +7
Large language models (LLMs) have demonstrated impressive capabilities in code generation by leveraging retrieval-augmented generation (RAG) methods. However, the computational cos…
Advances and Frontiers of LLM-based Issue Resolution in Software Engineering: A Comprehensive Survey
Caihua Li, Lianghong Guo, Yanlin Wang +9
Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment…
SimpleDevQA: Benchmarking Large Language Models on Development Knowledge QA
Jing Zhang, Lianghong Guo, Yanlin Wang +7
The Development Knowledge Question Answering (Dev Knowledge QA) task aims to provide natural language answers to knowledge-seeking questions during software development. To investi…
OmniGIRL: A Multilingual and Multimodal Benchmark for GitHub Issue Resolution
Lianghong Guo, Wei Tao, Runhan Jiang +7
The GitHub issue resolution task aims to resolve issues reported in repositories automatically. With advances in large language models (LLMs), this task has gained increasing atten…
Towards an Understanding of Context Utilization in Code Intelligence
Yanlin Wang, Kefeng Duan, Dewu Zheng +9
Code intelligence is an emerging domain in software engineering, aiming to improve the effectiveness and efficiency of various code-related tasks. Recent research suggests that inc…
Top General Performance = Top Domain Performance? DomainCodeBench: A Multi-domain Code Generation Benchmark
Dewu Zheng, Yanlin Wang, Ensheng Shi +4
With the rapid advancement of large language models (LLMs), extensive research has been conducted to investigate the code generation capabilities of LLMs. However, existing efforts…
RepoTransBench: A Real-World Multilingual Benchmark for Repository-Level Code Translation
Yanli Wang, Yanlin Wang, Suiquan Wang +8
Repository-level code translation refers to translating an entire code repository from one programming language to another while preserving the functionality of the source reposito…
RLCoder: Reinforcement Learning for Repository-Level Code Completion
Yanlin Wang, Yanli Wang, Daya Guo +4
Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrieval-augme…
HumanEvo: An Evolution-aware Benchmark for More Realistic Evaluation of Repository-level Code Generation
Dewu Zheng, Yanlin Wang, Ensheng Shi +4
To evaluate the repository-level code generation capabilities of Large Language Models (LLMs) in complex real-world software development scenarios, many evaluation methods have bee…
SparseCoder: Identifier-Aware Sparse Transformer for File-Level Code Summarization
Yanlin Wang, Yanxian Huang, Daya Guo +2
Code summarization aims to generate natural language descriptions of source code, facilitating programmers to understand and maintain it rapidly. While previous code summarization…
KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation
Wei Tao, Yucheng Zhou, Yanlin Wang +3
Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods…