3 citations · 11 across the 21 of their papers we have counts for
10 papers · 1 filter
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…