2 citations · 11 across the 51 of their papers we have counts for
23 papers · 1 filter
Speculative Forking: Turning Idle Wait into Parallel Exploration for Repository Environment Setup
Yuling Shi, Mingchu Zhong, Zhensu Sun +8
Before developers can use a software project, they must first get it to run. This often requires installing the right language runtime, system packages, build tools, and test comma…
SWE-at-Scale: Scalable Issue Synthesis from Historical Bug Fixes
Silin Chen, Zihan Zhang, Xiaodong Gu +7
As coding agents become increasingly capable, robust evaluation requires a broader and more diverse supply of verifiable software engineering (SWE) tasks. However, real-world tasks…
DeepRepoQA: Code Repository Question Answering with Deep Agent Exploration
Weihan Peng, Yuling Shi, Yingwei Ma +3
Answering developer questions about a software repository is a critical yet under-explored problem in software engineering. While existing repository understanding methods have adv…
Schrödinger's Code Repository: Have LLMs Learned SWE-bench or Memorized It?
Silin Chen, Yufei Yang, Xiaodong Gu +3
Repository-level coding benchmarks have become the standard for evaluating coding agents, yet they inherently suffer from data leakage because they are built upon popular open-sour…
Repo0: Design-Driven Zero-to-All Code Generation
Silin Chen, Haoyi Teng, Xiaodong Gu +5
Large language model agents have made substantial progress in code generation, yet most existing systems assume a predefined repository architecture. This assumption does not hold…
SkillForge: Self-Distilling Agents for Project-Specific Issue Resolution
Silin Chen, Han Li, Xiaodong Gu +2
Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to resolve issues in a specific rep…
Are Performance-Optimization Benchmarks Reliably Measuring Coding Agents?
Zhi Chen, Zhensu Sun, Yuling Shi +2
Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents by applying patches to real repositories and comparing runtime a…
Know Before Fix: QA-Driven Repository Knowledge Acquisition for Software Issue Resolution
Haotian Lin, Silin Chen, Xiaodong Gu +8
LLM-based coding agents have significantly advanced automated software issue resolution, yet they remain highly prone to factual errors caused by insufficient repository understand…
FastContext: Training Efficient Repository Explorer for Coding Agents
Shaoqiu Zhang, Maoquan Wang, Yuling Shi +12
Large Language Model (LLM) coding agents have achieved strong results on software engineering tasks, yet repository exploration remains a major bottleneck: locating relevant code c…
Dockerless: Environment-Free Program Verifier for Coding Agents
Wenhao Zeng, Yuling Shi, Xiaodong Gu +10
Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewards for reinforcement learning…
SWE-Explore: Benchmarking How Coding Agents Explore Repositories
Shaoqiu Zhang, Yuhang Wang, Jialiang Liang +8
Repository-level coding benchmarks such as SWE-bench have driven a rapid surge in the capabilities of coding agents. Yet they usually treat coding tasks as a holistic, binary predi…
LLM Agents Can See Code Repositories
Dongjian Ma, Silin Chen, Yufei Yang +3
Coding agents powered by large language models have demonstrated strong performance on software engineering tasks. Yet most agents consume repositories almost entirely as text, whi…
ClassEval-Pro: A Cross-Domain Benchmark for Class-Level Code Generation
Yeheng Chen, Chaoxiang Xie, Yuling Shi +4
LLMs have achieved strong results on both function-level code synthesis and repository-level code modification, yet a capability that falls between these two extremes -- compositio…
EffiSkill: Agent Skill Based Automated Code Efficiency Optimization
Zimu Wang, Yuling Shi, Mengfan Li +4
Code efficiency is a fundamental aspect of software quality, yet how to harness large language models (LLMs) to optimize programs remains challenging. Prior approaches have sought…
Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation
Pengyu Chang, Yixiong Fang, Silin Chen +3
Software testing is a critical, yet resource-intensive phase of the software development lifecycle. Over the years, various automated tools have been developed to aid in this proce…
Rethinking the Value of Agent-Generated Tests for LLM-Based Software Engineering Agents
Zhi Chen, Zhensu Sun, Yuling Shi +4
Large Language Model (LLM) code agents increasingly resolve repository-level issues by iteratively editing code, invoking tools, and validating candidate patches. In these workflow…
Rethinking Code Complexity Through the Lens of Large Language Models
Chen Xie, Xiaodong Gu, Yuling Shi +1
Code complexity metrics such as cyclomatic complexity have long been used to assess software quality and maintainability. With the rapid advancement of large language models (LLMs)…
SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
Yuhang Wang, Yuling Shi, Mo Yang +7
LLM agents have demonstrated remarkable capabilities in software development, but their performance is hampered by long interaction contexts, which incur high API costs and latency…
In Line with Context: Repository-Level Code Generation via Context Inlining
Chao Hu, Wenhao Zeng, Yuling Shi +2
Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model to understand the entire repository,…
EvoC2Rust: A Skeleton-guided Framework for Project-Level C-to-Rust Translation
Chaofan Wang, Tingrui Yu, Beijun Shen +6
Translating legacy C codebases to Rust is increasingly demanded for building safety-critical systems. While various approaches have emerged for this task, they face inherent trade-…
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Han Li, Yuling Shi, Shaoxin Lin +6
Issue resolution has made remarkable progress thanks to the advanced reasoning capabilities of large language models (LLMs). Recently, agent-based frameworks such as SWE-agent have…
SWE-Exp: Experience-Driven Software Issue Resolution
Silin Chen, Shaoxin Lin, Yuling Shi +8
Recent advances in large language model (LLM) agents have shown remarkable progress in software issue resolution, leveraging advanced techniques such as multi-agent collaboration a…
Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers
Yuling Shi, Hongyu Zhang, Chengcheng Wan +1
Large language models have catalyzed an unprecedented wave in code generation. While achieving significant advances, they blur the distinctions between machine- and human-authored…