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ORCIDLLM4CODE@ICSE 2025: Ottawa, ON, Canada
- IEEE/ACM International Workshop on Large Language Models for Code, LLM4Code@ICSE 2025, Ottawa, ON, Canada, May 3, 2025. IEEE 2025, ISBN 979-8-3315-2615-3
- Daniel Ramos, Cláudia Mamede, Kush Jain, Paulo Canelas, Catarina Gamboa, Claire Le Goues:
Are Large Language Models Memorizing Bug Benchmarks? 1-8 - André Silva, Martin Monperrus:
RepairBench: Leaderboard of Frontier Models for Program Repair. 9-16 - Hyunjoon Cho, Sungmin Kang, Gabin An, Shin Yoo:
COSMosFL: Ensemble of Small Language Models for Fault Localisation. 17-24 - Amy Munson, Juanita Gomez, Alvaro A. Cárdenas:
♪ With a Little Help from My (LLM) Friends: Enhancing Static Analysis with LLMs to Detect Software Vulnerabilities. 25-32 - Jinjun Peng, Leyi Cui, Kele Huang, Junfeng Yang, Baishakhi Ray:
CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation. 33-40 - Daniele Cipollone, Changjie Wang, Mariano Scazzariello, Simone Ferlin, Maliheh Izadi, Dejan Kostic, Marco Chiesa:
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues. 41-48 - Farima Farmahinifarahani, Petr Babkin, Salwa Alamir, Xiaomo Liu:
From Zero to Sixty at the Speed of RAG: Improving YAML Recipe Generation via Retrieval. 49-56 - Shihao Xia, Mengting He, Linhai Song, Yiying Zhang:
SC-Bench: A Large-Scale Dataset for Smart Contract Auditing. 57-64 - Aaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse:
Training LLMs for Generating IEC 61131-3 Structured Text with Online Feedback. 65-71 - Quinn Dougherty, Ronak Mehta:
Proving the Coding Interview: A Benchmark for Formally Verified Code Generation. 72-79 - Md. S. Hossain, Anika Tabassum, Md. Fahim Arefin, Tarannum Shaila Zaman:
LLM-ProS: Analyzing Large Language Models' Performance in Competitive Problem Solving. 80-87 - Aidar Valeev, Roman Garaev, Vadim Lomshakov, Irina Piontkovskaya, Vladimir Ivanov, Israel Adewuyi:
YABLoCo: Yet Another Benchmark for Long Context Code Generation. 88-95 - Jan Kels, Abdelhalim Hafedh Dahou, Brigitte Mathiak:
Evaluating Language Models for Computer Graphics Code Completion. 96-103 - Mahmoud Jahanshahi, Audris Mockus:
Cracks in The Stack: Hidden Vulnerabilities and Licensing Risks in LLM Pre-Training Datasets. 104-111 - Naman Agrawal, Ridwan Shariffdeen, Guanlin Wang, Sanka Rasnayaka, Ganesh Neelakanta Iyer:
Analysis of Student-LLM Interaction in a Software Engineering Project. 112-119 - Hyeonseok Lee, Gabin An, Shin Yoo:
Metamon: Finding Inconsistencies between Program Documentation and Behavior using Metamorphic LLM Queries. 120-127 - Claas Beger, Saikat Dutta:
CoCoNUT: Structural Code Understanding does not fall out of a tree. 128-136 - Murtuza Shahzad, Joseph Wilson, Ibrahim Al Azher, Hamed Alhoori, Mona Rahimi:
From Theory to Practice: Code Generation Using LLMs for CAPEC and CWE Frameworks. 137-144 - Nilesh Dhulshette, Sapan Shah, Vinay Kulkarni:
Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMs. 145-152 - Vladimir Makharev, Vladimir Ivanov:
Code Summarization Beyond Function Level. 153-160 - Sanyogita Piya, Anahita Samadi, Allison Sullivan:
Is More or Less Automation Better? An Investigation into the LLM4TDD Process. 161-168 - Mihir Athale, Vishal Vaddina:
Knowledge Graph Based Repository-Level Code Generation. 169-176 - Colin Diggs, Michael Doyle, Amit Madan, Eric O. Scott, Emily Escamilla, Jacob Zimmer, Naveed Nekoo, Paul Ursino, Michael Bartholf, Zachary Robin, Anand Patel, Chris Glasz, William Macke, Paul Kirk, Jasper Phillips, Arun Sridharan, Doug Wendt, Scott Rosen, Nitin Naik, Justin F. Brunelle, Samruddhi Thaker:
Leveraging LLMs for Legacy Code Modernization: Evaluation of LLM-Generated Documentation. 177-184 - Laura Puccioni, Alireza Farshin, Mariano Scazzariello, Changjie Wang, Marco Chiesa, Dejan Kostic:
Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning. 185-192 - Srivishnu Pyda, Daniel Nichols, Abhinav Bhatele:
The Shortcomings of Code LLMs in Modeling Code Properties. 193-199 - Yifan Zong, Yuntian Deng, Pengyu Nie:
Mix-of-Language-Experts Architecture for Multilingual Programming. 200-208 - Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu:
Do Code LLMs Understand Design Patterns? 209-212 - Changjie Wang, Mariano Scazzariello, Marco Chiesa:
From Scientific Texts to Verifiable Code: Automating the Process with Transformers. 213-216
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