Leveraging Language Models for Log Statement Generation in Multilingual Scenarios: How Far Are We?
Fuente:
arXiv
Saved in:
| Main Authors: | Kusama, Kazuki, Shu, Honglin, Kondo, Masanari, Kamei, Yasutaka |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair
by: Kusama, Kazuki, et al.
Published: (2025)
by: Kusama, Kazuki, et al.
Published: (2025)
Large Language Models for Equivalent Mutant Detection: How Far Are We?
by: Tian, Zhao, et al.
Published: (2024)
by: Tian, Zhao, et al.
Published: (2024)
How Far Have LLMs Come Toward Automated SATD Taxonomy Construction?
by: Nakashima, Sota, et al.
Published: (2025)
by: Nakashima, Sota, et al.
Published: (2025)
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
by: wang, Dong, et al.
Published: (2025)
by: wang, Dong, et al.
Published: (2025)
A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection
by: Yu, Junji, et al.
Published: (2025)
by: Yu, Junji, et al.
Published: (2025)
Evaluating Large Language Models for Multilingual Vulnerability Detection at Dual Granularities
by: Shu, Honglin, et al.
Published: (2025)
by: Shu, Honglin, et al.
Published: (2025)
Leveraging Mutation Analysis for LLM-based Repair of Quantum Programs
by: Yoshida, Chihiro, et al.
Published: (2026)
by: Yoshida, Chihiro, et al.
Published: (2026)
Why Agentic-PRs Get Rejected: A Comparative Study of Coding Agents
by: Nakashima, Sota, et al.
Published: (2026)
by: Nakashima, Sota, et al.
Published: (2026)
An Empirical Study of Token-based Micro Commits
by: Kondo, Masanari, et al.
Published: (2024)
by: Kondo, Masanari, et al.
Published: (2024)
An empirical study on declined proposals: why are these proposals declined?
by: Kondo, Masanari, et al.
Published: (2025)
by: Kondo, Masanari, et al.
Published: (2025)
OSS Myths and Facts
by: Iimura, Yukako, et al.
Published: (2024)
by: Iimura, Yukako, et al.
Published: (2024)
Myth: The loss of core developers is a critical issue for OSS communities
by: Nourry, Olivier, et al.
Published: (2024)
by: Nourry, Olivier, et al.
Published: (2024)
Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot
by: Koyanagi, Kei, et al.
Published: (2024)
by: Koyanagi, Kei, et al.
Published: (2024)
"Refactoring Runaway": Understanding and Mitigating Tangled Refactorings in Coding Agents for Issue Resolution
by: Tian, Zhao, et al.
Published: (2026)
by: Tian, Zhao, et al.
Published: (2026)
Toward Linking Declined Proposals and Source Code: An Exploratory Study on the Go Repository
by: Nakashima, Sota, et al.
Published: (2026)
by: Nakashima, Sota, et al.
Published: (2026)
AILINKPREVIEWER: Enhancing Code Reviews with LLM-Powered Link Previews
by: Trakoolgerntong, Panya, et al.
Published: (2025)
by: Trakoolgerntong, Panya, et al.
Published: (2025)
Evaluating Mutation-based Fault Localization for Quantum Programs
by: Ishimoto, Yuta, et al.
Published: (2025)
by: Ishimoto, Yuta, et al.
Published: (2025)
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
by: Jiang, Zhihan, et al.
Published: (2023)
by: Jiang, Zhihan, et al.
Published: (2023)
Unraveling the Potential of Large Language Models in Code Translation: How Far Are We?
by: Tao, Qingxiao, et al.
Published: (2024)
by: Tao, Qingxiao, et al.
Published: (2024)
Go Static: Contextualized Logging Statement Generation
by: Li, Yichen, et al.
Published: (2024)
by: Li, Yichen, et al.
Published: (2024)
Can AI Agents Generate Microservices? How Far are We?
by: Adnan, Bassam, et al.
Published: (2026)
by: Adnan, Bassam, et al.
Published: (2026)
Vulnerability Detection with Code Language Models: How Far Are We?
by: Ding, Yangruibo, et al.
Published: (2024)
by: Ding, Yangruibo, et al.
Published: (2024)
Specification-Driven Code Translation Powered by Large Language Models: How Far Are We?
by: Saha, Soumit Kanti, et al.
Published: (2024)
by: Saha, Soumit Kanti, et al.
Published: (2024)
Larger Is Not Always Better: Exploring Small Open-source Language Models in Logging Statement Generation
by: Zhong, Renyi, et al.
Published: (2025)
by: Zhong, Renyi, et al.
Published: (2025)
FastLog: An End-to-End Method to Efficiently Generate and Insert Logging Statements
by: Xie, Xiaoyuan, et al.
Published: (2023)
by: Xie, Xiaoyuan, et al.
Published: (2023)
Retrieval-Augmented Test Generation: How Far Are We?
by: Shin, Jiho, et al.
Published: (2024)
by: Shin, Jiho, et al.
Published: (2024)
Duplicate Bug Report Detection: How Far Are We?
by: Zhang, Ting, et al.
Published: (2022)
by: Zhang, Ting, et al.
Published: (2022)
Vulnerability-Affected Versions Identification: How Far Are We?
by: Chen, Xingchu, et al.
Published: (2025)
by: Chen, Xingchu, et al.
Published: (2025)
Deep Learning Framework Testing via Model Mutation: How Far Are We?
by: Mu, Yanzhou, et al.
Published: (2025)
by: Mu, Yanzhou, et al.
Published: (2025)
LogUpdater: Automated Detection and Repair of Specific Defects in Logging Statements
by: Zhong, Renyi, et al.
Published: (2024)
by: Zhong, Renyi, et al.
Published: (2024)
An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far Are We?
by: Suh, Hyunjae, et al.
Published: (2024)
by: Suh, Hyunjae, et al.
Published: (2024)
Automated Testing of Task-based Chatbots: How Far Are We?
by: Clerissi, Diego, et al.
Published: (2026)
by: Clerissi, Diego, et al.
Published: (2026)
Representation Learning for Stack Overflow Posts: How Far are We?
by: He, Junda, et al.
Published: (2023)
by: He, Junda, et al.
Published: (2023)
LLM For Loop Invariant Generation and Fixing: How Far Are We?
by: Akhond, Mostafijur Rahman, et al.
Published: (2025)
by: Akhond, Mostafijur Rahman, et al.
Published: (2025)
Model Editing for LLMs4Code: How Far are We?
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
Measuring Emergent Capabilities of LLMs for Software Engineering: How Far Are We?
by: O'Brien, Conor, et al.
Published: (2024)
by: O'Brien, Conor, et al.
Published: (2024)
How Far Have We Gone in Binary Code Understanding Using Large Language Models
by: Shang, Xiuwei, et al.
Published: (2024)
by: Shang, Xiuwei, et al.
Published: (2024)
How Far Can We Go with Practical Function-Level Program Repair?
by: Xiang, Jiahong, et al.
Published: (2024)
by: Xiang, Jiahong, et al.
Published: (2024)
Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem
by: Xiao, Tao, et al.
Published: (2026)
by: Xiao, Tao, et al.
Published: (2026)
When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?
by: Chen, Chong, et al.
Published: (2023)
by: Chen, Chong, et al.
Published: (2023)
Similar Items
-
How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair
by: Kusama, Kazuki, et al.
Published: (2025) -
Large Language Models for Equivalent Mutant Detection: How Far Are We?
by: Tian, Zhao, et al.
Published: (2024) -
How Far Have LLMs Come Toward Automated SATD Taxonomy Construction?
by: Nakashima, Sota, et al.
Published: (2025) -
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
by: wang, Dong, et al.
Published: (2025) -
A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection
by: Yu, Junji, et al.
Published: (2025)