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References (19)

[1]
SWE-Refactor: A Repository-Level Benchmark for Real-World LLM-Based Code Refactoring
2026Yisen Xu, Jinqiu Yang et al.
[2]
SecureAgentBench: Benchmarking Secure Code Generation under Realistic Vulnerability Scenarios
2025Junkai Chen, Huihui Huang et al.
[3]
Research: A Tool and Workflow for Benchmarking LLM-Based Code Improvements
2025Zeineb Rejiba, Raphael Eidenbenz et al.
[4]
SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents
2025Ibragim Badertdinov, Alexander Golubev et al.
[5]
Refactoring Codebases through Library Design
2025Ziga Kovacic, Celine Lee et al.
[6]
RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code
2025Dhruv Gautam, Spandan Garg et al.
[7]
FEA-Bench: A Benchmark for Evaluating Repository-Level Code Generation for Feature Implementation
2025Wei Li, Xin Zhang et al.
[8]
Exploring the potential of general purpose LLMs in automated software refactoring: an empirical study
2025Bo Liu, Yanjie Jiang et al.
[9]
Can Language Models Replace Programmers for Coding? REPOCOD Says 'Not Yet'
2025Shanchao Liang, Nan Jiang et al.
[10]
An Empirical Study on the Code Refactoring Capability of Large Language Models
2024Jonathan Cordeiro, Shayan Noei et al.
[11]
Next-Generation Refactoring: Combining LLM Insights and IDE Capabilities for Extract Method
2024Dorin Pomian, Abhiram Bellur et al.
[12]
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
2024Niels Mündler, Mark Niklas Müller et al.
[13]
Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
2023Federico Cassano, Luisa Li et al.
[14]
Refactoring Programs Using Large Language Models with Few-Shot Examples
2023Atsushi Shirafuji, Yusuke Oda et al.
[15]
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
2023Carlos E. Jimenez, John Yang et al.
[16]
GitHub
2022Sufyan bin Uzayr
[17]
Introducing
2011Lorenzo Veracini
[18]
Create.
2009Ron Wolfson
[19]
Acm Sigsoft Software Engineering Notes Vol 17 No 4 Foundations for the Study of Software Architecture
D. Perry, A. Wolf

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10

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5

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