activity
20232026
most citedA Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

23 citations · 68 across the 41 of their papers we have counts for

collaborators
Showing 2026 · cs.SEShow all

7 papers · 2 filters

cs.SE2026

SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents

Xin He, Yanlin Wang, Mingwei Liu +3

Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pa…

cs.SE2026

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

Kefeng Duan, Dewu Zheng, Yanlin Wang +7

Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and test execution. Existing effici…

cs.SE2026

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…

cs.SE2026

WebDesignIter: Co-Evolving Design Knowledge for Repository-Level Front-End Code Generation

Zheng Pei, Mingwei Liu, Zhenxi Chen +2

Front-end development accumulates change after change at the repository level, weaving complex cross-file dependencies that current LLM coding agents tuned for single-shot tasks ca…

cs.SE2026

Dynamic analysis enhances issue resolution

Mingwei Liu, Zihao Wang, Zhenxi Chen +3

Resolving complex code defects from natural language descriptions remains a fundamental software engineering challenge. Recently, large language models (LLMs) have driven the creat…

cs.SE2026

ShortCoder: Knowledge-Augmented Syntax Optimization for Token-Efficient Code Generation

Sicong Liu, Yanxian Huang, Mingwei Liu +6

Code generation tasks aim to automate the conversion of user requirements into executable code, significantly reducing manual development efforts and enhancing software productivit…