Cover Image

Are They All Good? Evaluating the Quality of CoTs in LLM-based Code Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Binquan, Zhang, Li, Luo, Zhiwen, Du, Yuxin, Liu, Fang, Wang, Song, Shi, Lin
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Empirical Study of Interaction Smells in Multi-Turn Human-LLM Collaborative Code Generation
by: Zhang, Binquan, et al.
Published: (2026)

Decoding Human-LLM Collaboration in Coding: An Empirical Study of Multi-Turn Conversations in the Wild
by: Zhang, Binquan, et al.
Published: (2025)

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length
by: Cheng, Junhang, et al.
Published: (2025)

Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code
by: Liu, Yang, et al.
Published: (2026)

CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation
by: Huang, Dong, et al.
Published: (2023)

The Good, the Bad, and the Missing: Neural Code Generation for Machine Learning Tasks
by: Shin, Jiho, et al.
Published: (2023)

On the Road to Personalized Code Intelligence: Portraiting and Assisting Developers Based on Their In-IDE Behaviors
by: Liu, Yuhong, et al.
Published: (2026)

Human-Like Code Quality Evaluation through LLM-based Recursive Semantic Comprehension
by: Xu, Fangzhou, et al.
Published: (2024)

LAURA: Enhancing Code Review Generation with Context-Enriched Retrieval-Augmented LLM
by: Zhang, Yuxin, et al.
Published: (2025)

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution
by: Wang, Yibo, et al.
Published: (2025)

CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation
by: Pan, Ruwei, et al.
Published: (2025)

Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Code
by: Liu, Fang, et al.
Published: (2024)

CodeArena: A Collective Evaluation Platform for LLM Code Generation
by: Du, Mingzhe, et al.
Published: (2025)

GraphCodeAgent: Dual Graph-Guided LLM Agent for Retrieval-Augmented Repo-Level Code Generation
by: Li, Jia, et al.
Published: (2025)

Uncovering Weaknesses in Neural Code Generation
by: Lian, Xiaoli, et al.
Published: (2024)

Are Human Rules Necessary? Generating Reusable APIs with CoT Reasoning and In-Context Learning
by: Mai, Yubo, et al.
Published: (2024)

On Evaluating the Efficiency of Source Code Generated by LLMs
by: Niu, Changan, et al.
Published: (2024)

Inducing Vulnerable Code Generation in LLM Coding Assistants
by: Zeng, Binqi, et al.
Published: (2025)

CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation
by: Wang, Peiding, et al.
Published: (2025)

RepoScope: Leveraging Call Chain-Aware Multi-View Context for Repository-Level Code Generation
by: Liu, Yang, et al.
Published: (2025)

No Need to Lift a Finger Anymore? Assessing the Quality of Code Generation by ChatGPT
by: Liu, Zhijie, et al.
Published: (2023)

One Size Does Not Fit All: Investigating Efficacy of Perplexity in Detecting LLM-Generated Code
by: Xu, Jinwei, et al.
Published: (2024)

LLMs Meet Library Evolution: Evaluating Deprecated API Usage in LLM-based Code Completion
by: Wang, Chong, et al.
Published: (2024)

Bias Unveiled: Investigating Social Bias in LLM-Generated Code
by: Ling, Lin, et al.
Published: (2024)

Benchmarking and Studying the LLM-based Code Review
by: Zeng, Zhengran, et al.
Published: (2025)

SolSearch: An LLM-Driven Framework for Efficient SAT-Solving Code Generation
by: Sheng, Junjie, et al.
Published: (2025)

Evaluating and Achieving Controllable Code Completion in Code LLM
by: Zhang, Jiajun, et al.
Published: (2026)

Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks
by: Mohseni, Seyedreza, et al.
Published: (2026)

DSL or Code? Evaluating the Quality of LLM-Generated Algebraic Specifications: A Case Study in Optimization at Kinaxis
by: Ayoughi, Negin, et al.
Published: (2026)

TestART: Improving LLM-based Unit Testing via Co-evolution of Automated Generation and Repair Iteration
by: Gu, Siqi, et al.
Published: (2024)

CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation
by: Wang, Peiding, et al.
Published: (2026)

Whose fault is it anyway? SILC: Safe Integration of LLM-Generated Code
by: Lin, Peisen, et al.
Published: (2024)

ReVul-CoT: Towards Effective Software Vulnerability Assessment with Retrieval-Augmented Generation and Chain-of-Thought Prompting
by: Chen, Zhijie, et al.
Published: (2025)

Prompt-based Code Completion via Multi-Retrieval Augmented Generation
by: Tan, Hanzhuo, et al.
Published: (2024)

Code Copycat Conundrum: Demystifying Repetition in LLM-based Code Generation
by: Liu, Mingwei, et al.
Published: (2025)

Probing Privacy Leaks in LLM-based Code Generation via Test Generation
by: Ge, Yifei, et al.
Published: (2026)

Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
by: He, Mengliang, et al.
Published: (2025)

Benchmarking Requirement-to-Architecture Generation with Hybrid Evaluation
by: Li, Minxiao, et al.
Published: (2026)

Too Noisy To Learn: Enhancing Data Quality for Code Review Comment Generation
by: Liu, Chunhua, et al.
Published: (2025)

Multi-LLM Orchestration for High-Quality Code Generation: Exploiting Complementary Model Strengths
by: Chen, Huashan, et al.
Published: (2025)