Saved in:
| Main Authors: | Twist, Lukas, Zhang, Jie M., Harman, Mark, Syme, Don, Noppen, Joost, Yannakoudakis, Helen, Nauck, Detlef |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.17181 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Study of Library Usage in Agent-Authored Pull Requests
by: Twist, Lukas, et al.
Published: (2025)
by: Twist, Lukas, et al.
Published: (2025)
Summary-Mediated Repair: Can LLMs use code summarisation as a tool for program repair?
by: Twist, Lukas
Published: (2025)
by: Twist, Lukas
Published: (2025)
SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering
by: Gong, Jingzhi, et al.
Published: (2026)
by: Gong, Jingzhi, et al.
Published: (2026)
Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges
by: Harman, Mark, et al.
Published: (2025)
by: Harman, Mark, et al.
Published: (2025)
Generative AI for Testing of Autonomous Driving Systems: A Survey
by: Song, Qunying, et al.
Published: (2025)
by: Song, Qunying, et al.
Published: (2025)
Fairness Improvement with Multiple Protected Attributes: How Far Are We?
by: Chen, Zhenpeng, et al.
Published: (2023)
by: Chen, Zhenpeng, et al.
Published: (2023)
MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair
by: Dehghan, Meghdad, et al.
Published: (2024)
by: Dehghan, Meghdad, et al.
Published: (2024)
The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project
by: Gröpler, Robin, et al.
Published: (2025)
by: Gröpler, Robin, et al.
Published: (2025)
Evaluating the Generalizability of LLMs in Automated Program Repair
by: Li, Fengjie, et al.
Published: (2025)
by: Li, Fengjie, et al.
Published: (2025)
Utilizing LLMs for Industrial Process Automation: A Case Study on Modifying RAPID Programs
by: Fares, Salim, et al.
Published: (2025)
by: Fares, Salim, et al.
Published: (2025)
The Hitchhiker's Guide to Program Analysis, Part II: Deep Thoughts by LLMs
by: Li, Haonan, et al.
Published: (2025)
by: Li, Haonan, et al.
Published: (2025)
CAKE: Cloud Architecture Knowledge Evaluation of Large Language Models
by: Adam, Tim Lukas, et al.
Published: (2026)
by: Adam, Tim Lukas, et al.
Published: (2026)
Reducing False Positives in Static Bug Detection with LLMs: An Empirical Study in Industry
by: Du, Xueying, et al.
Published: (2026)
by: Du, Xueying, et al.
Published: (2026)
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
by: Wen, Xin-Cheng, et al.
Published: (2025)
by: Wen, Xin-Cheng, et al.
Published: (2025)
Mastering the Craft of Data Synthesis for CodeLLMs
by: Chen, Meng, et al.
Published: (2024)
by: Chen, Meng, et al.
Published: (2024)
Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
by: Ashraf, Humza, et al.
Published: (2025)
by: Ashraf, Humza, et al.
Published: (2025)
RuleFlow : Generating Reusable Program Optimizations with LLMs
by: Singh, Avaljot, et al.
Published: (2026)
by: Singh, Avaljot, et al.
Published: (2026)
AbstractBeam: Enhancing Bottom-Up Program Synthesis using Library Learning
by: Zenkner, Janis, et al.
Published: (2024)
by: Zenkner, Janis, et al.
Published: (2024)
Model See, Model Do? Exposure-Aware Evaluation of Bug-vs-Fix Preference in Code LLMs
by: Al-Kaswan, Ali, et al.
Published: (2026)
by: Al-Kaswan, Ali, et al.
Published: (2026)
CangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language
by: Cheng, Junhang, et al.
Published: (2026)
by: Cheng, Junhang, et al.
Published: (2026)
LLMs Lean on Priors, Not Programming Language Semantics
by: Thimmaiah, Aditya, et al.
Published: (2025)
by: Thimmaiah, Aditya, et al.
Published: (2025)
EduBot -- Can LLMs Solve Personalized Learning and Programming Assignments?
by: Wang, Yibin, et al.
Published: (2025)
by: Wang, Yibin, et al.
Published: (2025)
A Survey Study on the State of the Art of Programming Exercise Generation using Large Language Models
by: Frankford, Eduard, et al.
Published: (2024)
by: Frankford, Eduard, et al.
Published: (2024)
Planning-Driven Programming: A Large Language Model Programming Workflow
by: Lei, Chao, et al.
Published: (2024)
by: Lei, Chao, et al.
Published: (2024)
ProgramBench: Can Language Models Rebuild Programs From Scratch?
by: Yang, John, et al.
Published: (2026)
by: Yang, John, et al.
Published: (2026)
RefusalBench: Why Refusal Rate Misranks Frontier LLMs on Biological Research Prompts
by: Weidener, Lukas, et al.
Published: (2026)
by: Weidener, Lukas, et al.
Published: (2026)
RAG-Verus: Repository-Level Program Verification with LLMs using Retrieval Augmented Generation
by: Zhong, Sicheng, et al.
Published: (2025)
by: Zhong, Sicheng, et al.
Published: (2025)
Personality-Guided Code Generation Using Large Language Models
by: Guo, Yaoqi, et al.
Published: (2024)
by: Guo, Yaoqi, et al.
Published: (2024)
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
by: Pan, Chenkai, et al.
Published: (2026)
by: Pan, Chenkai, et al.
Published: (2026)
Mutation-Guided LLM-based Test Generation at Meta
by: Foster, Christopher, et al.
Published: (2025)
by: Foster, Christopher, et al.
Published: (2025)
Do Current Language Models Support Code Intelligence for R Programming Language?
by: Zhao, ZiXiao, et al.
Published: (2024)
by: Zhao, ZiXiao, et al.
Published: (2024)
Learning to Code with Context: A Study-Based Approach
by: Borghoff, Uwe M., et al.
Published: (2025)
by: Borghoff, Uwe M., et al.
Published: (2025)
When Fuzzing Meets LLMs: Challenges and Opportunities
by: Jiang, Yu, et al.
Published: (2024)
by: Jiang, Yu, et al.
Published: (2024)
CodeGRAG: Bridging the Gap between Natural Language and Programming Language via Graphical Retrieval Augmented Generation
by: Du, Kounianhua, et al.
Published: (2024)
by: Du, Kounianhua, et al.
Published: (2024)
LibRec: Benchmarking Retrieval-Augmented LLMs for Library Migration Recommendations
by: Han, Junxiao, et al.
Published: (2025)
by: Han, Junxiao, et al.
Published: (2025)
CrossPL: Evaluating Large Language Models on Cross Programming Language Code Generation
by: Xiong, Zhanhang, et al.
Published: (2025)
by: Xiong, Zhanhang, et al.
Published: (2025)
Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
by: Cao, Yuhan, et al.
Published: (2025)
by: Cao, Yuhan, et al.
Published: (2025)
LLMs: A Game-Changer for Software Engineers?
by: Haque, Md Asraful
Published: (2024)
by: Haque, Md Asraful
Published: (2024)
Architecture Without Architects: How AI Coding Agents Shape Software Architecture
by: Konrad, Phongsakon Mark, et al.
Published: (2026)
by: Konrad, Phongsakon Mark, et al.
Published: (2026)
An Empirical Study of the Non-determinism of ChatGPT in Code Generation
by: Ouyang, Shuyin, et al.
Published: (2023)
by: Ouyang, Shuyin, et al.
Published: (2023)
Similar Items
-
A Study of Library Usage in Agent-Authored Pull Requests
by: Twist, Lukas, et al.
Published: (2025) -
Summary-Mediated Repair: Can LLMs use code summarisation as a tool for program repair?
by: Twist, Lukas
Published: (2025) -
SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering
by: Gong, Jingzhi, et al.
Published: (2026) -
Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges
by: Harman, Mark, et al.
Published: (2025) -
Generative AI for Testing of Autonomous Driving Systems: A Survey
by: Song, Qunying, et al.
Published: (2025)