Title Authors
Analysis of Student-LLM Interaction in a Software Engineering Project Agrawal Naman, Ridwan Shariffdeen, Guanlin Wang, Sanka Rasnayaka, Ganesh Neelakanta Iyer
Are Large Language Models Memorizing Bug Benchmarks? Daniel Ramos, Claudia Mamede, Kush Jain, Paulo Canelas, Catarina Gamboa, Claire Le Goues
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues Daniele Cipollone, Changjie Wang, Mariano Scazzariello, Simone Ferlin, Maliheh Izadi, Dejan Kostic, Marco Chiesa
COSMosFL: Ensemble of Small Language Models for Fault Localisation Hyunjoon Cho, Sungmin Kang, Gabin An, Shin Yoo
CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation Jinjun Peng, Leyi Cui, Kele Huang, Junfeng Yang, Baishakhi Ray
CoCoNUT: Structural Code Understanding does not fall out of a tree Claas Beger, Saikat Dutta
Code Summarization Beyond Function Level Vladimir Makharev, Vladimir Ivanov
Cracks in The Stack: Hidden Vulnerabilities and Licensing Risks in LLM Pre-Training Datasets Mahmoud Jahanshahi, Audris Mockus
Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning Laura Puccioni, Alireza Farshin, Mariano Scazzariello, Changjie Wang, Marco Chiesa, Dejan Kostic
Do Code LLMs Understand Design Patterns? 💡 Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu
Evaluating Language Models for Computer Graphics Code Completion Jan Kels, Abdelhalim Dahou, Brigitte Mathiak
From Scientific Texts to Verifiable Code: Automating the Process with Transformers 💡 Changjie Wang, Mariano Scazzariello, Marco Chiesa
From Theory to Practice: Code Generation Using LLMs for CAPEC and CWE Frameworks Mohammed Murtuza Shahzad Syed, Joseph Wilson, Ibrahim Al Azher, Hamed Alhoori, Mona Rahimi
From Zero to Sixty at the Speed of RAG: Improving YAML Recipe Generation via Retrieval Farima Farmahinifarahani, Petr Babkin, Salwa Alamir, Xiaomo Liu
Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMs Nilesh Dhulshette, Sapan Shah, Vinay Kulkarni
Is More or Less Automation Better? An Investigation into the LLM4TDD Process Sanyogita Piya, Anahita Samadi, Allison Sullivan
Knowledge Graph Based Repository-Level Code Generation Mihir Athale, Vishal Vaddina
LLM-ProS: Analyzing Large Language Models’ Performance in Competitive Problem Solving Md Sifat Hossain, Anika Tabassum, Md. Fahim Arefin, Tarannum Shaila Zaman
Leveraging LLMs for Legacy Code Modernization: Evaluation of LLM-Generated Documentation Colin Diggs, Michael Doyle, Amit Madan, Emily Escamilla, Siggy Scott, 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
METAMON: Finding Inconsistencies between Program Documentation and Behavior using Metamorphic LLM Queries Hyunseok Lee, Gabin An, Shin Yoo
Mix-of-Language-Experts Architecture for Multilingual Programming Yifan Zong, Yuntian Deng, Pengyu Nie
Proving the Coding Interview: A Benchmark for Formally Verified Code Generation Quinn Dougherty, Ronak Mehta
RepairBench: Leaderboard of Frontier Models for Program Repair André Silva, Martin Monperrus
SC-Bench: A Large-Scale Dataset for Smart Contract Auditing Shihao Xia, Mengting He, Linhai Song, Yiying Zhang
Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis 🪧 Manish Shetty, Naman Jain, Adwait Godbole, Sanjit A. Seshia, Koushik Sen
Training LLMs for Generating IEC 61131-3 Structured Text with Online Feedback Aaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse
Understanding Code Properties: Is Code All You Need? Srivishnu Pyda, Daniel Nichols, Abhinav Bhatele
With a Little Help from My (LLM) Friends: Enhancing Static Analysis with LLMs to Detect Software Vulnerabilities Amy Munson, Juanita Gomez, Álvaro Cárdenas
YABLoCo: Yet Another Benchmark for Long Context Code Generation Aidar Valeev, Vladimir Ivanov, Roman Garaev, Vadim Lomshakov, Irina Pionkovskaya, Israel Adewuyi

Papers are sorted alphabetically (💡 denotes position papers and 🪧 denotes non-archival papers).