6 papers
Service Ecosystem Evolution: A Comprehensive Survey from Complex Network Perspectives
Shuiguang Deng, Xingliang Wang, Guochang Li +5
Digital society increasingly relies on complex service ecosystems, formed by interconnected services from technology giants. However, the growing scale and intricate dependencies o…
CodeGlance: Understanding Code Reasoning Challenges in LLMs through Multi-Dimensional Feature Analysis
Yunkun Wang, Xuanhe Zhang, Junxiao Han +2
In modern software development, developers frequently need to understand code behavior at a glance -- whether reviewing pull requests, debugging issues, or navigating unfamiliar co…
Empowering RepoQA-Agent based on Reinforcement Learning Driven by Monte-carlo Tree Search
Guochang Li, Yuchen Liu, Zhen Qin +7
Repository-level software engineering tasks require large language models (LLMs) to efficiently navigate and extract information from complex codebases through multi-turn tool inte…
InspectCoder: Dynamic Analysis-Enabled Self Repair through interactive LLM-Debugger Collaboration
Yunkun Wang, Yue Zhang, Guochang Li +5
Large Language Models (LLMs) frequently generate buggy code with complex logic errors that are challenging to diagnose. While existing LLM-based self-repair approaches conduct inte…
ExploraCoder: Advancing code generation for multiple unseen APIs via planning and chained exploration
Yunkun Wang, Yue Zhang, Zhen Qin +5
Large language models face intrinsic limitations in coding with APIs that are unseen in their training corpora. As libraries continuously evolve, it becomes impractical to exhausti…
Do Code LLMs Understand Design Patterns?
Zhenyu Pan, Xuefeng Song, Yunkun Wang +4
Code Large Language Models (LLMs) demonstrate great versatility in adapting to various downstream tasks, including code generation and completion, as well as bug detection and fixi…