Abstract is missing.
- Are Large Language Models Memorizing Bug Benchmarks?Daniel Ramos, Cláudia Mamede, Kush Jain, Paulo Canelas, Catarina Gamboa, Claire Le Goues. 1-8 [doi]
- RepairBench: Leaderboard of Frontier Models for Program RepairAndré Silva, Martin Monperrus. 9-16 [doi]
- COSMosFL: Ensemble of Small Language Models for Fault LocalisationHyunJoon Cho, Sungmin Kang, Gabin An, Shin Yoo. 17-24 [doi]
- ♪ With a Little Help from My (LLM) Friends: Enhancing Static Analysis with LLMs to Detect Software VulnerabilitiesAmy Munson, Juanita Gomez, Alvaro A. Cárdenas. 25-32 [doi]
- CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code GenerationJinjun Peng, Leyi Cui, Kele Huang, Junfeng Yang, Baishakhi Ray. 33-40 [doi]
- Automating the Detection of Code Vulnerabilities by Analyzing GitHub IssuesDaniele Cipollone, Changjie Wang, Mariano Scazzariello, Simone Ferlin, Maliheh Izadi, Dejan Kostic, Marco Chiesa. 41-48 [doi]
- From Zero to Sixty at the Speed of RAG: Improving YAML Recipe Generation via RetrievalFarima Farmahinifarahani, Petr Babkin, Salwa Alamir, Xiaomo Liu. 49-56 [doi]
- SC-Bench: A Large-Scale Dataset for Smart Contract AuditingShihao Xia, Mengting He, Linhai Song, Yiying Zhang 0005. 57-64 [doi]
- Training LLMs for Generating IEC 61131-3 Structured Text with Online FeedbackAaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse. 65-71 [doi]
- Proving the Coding Interview: A Benchmark for Formally Verified Code GenerationQuinn Dougherty, Ronak Mehta. 72-79 [doi]
- LLM-ProS: Analyzing Large Language Models' Performance in Competitive Problem SolvingMd. S. Hossain, Anika Tabassum, Md. Fahim Arefin, Tarannum Shaila Zaman. 80-87 [doi]
- YABLoCo: Yet Another Benchmark for Long Context Code GenerationAidar Valeev, Roman Garaev, Vadim Lomshakov, Irina Piontkovskaya, Vladimir Ivanov 0001, Israel Adewuyi. 88-95 [doi]
- Evaluating Language Models for Computer Graphics Code CompletionJan Kels, Abdelhalim Hafedh Dahou, Brigitte Mathiak. 96-103 [doi]
- Cracks in The Stack: Hidden Vulnerabilities and Licensing Risks in LLM Pre-Training DatasetsMahmoud Jahanshahi, Audris Mockus. 104-111 [doi]
- Analysis of Student-LLM Interaction in a Software Engineering ProjectNaman Agrawal, Ridwan Shariffdeen, Guanlin Wang, Sanka Rasnayaka, Ganesh Neelakanta Iyer. 112-119 [doi]
- Metamon: Finding Inconsistencies between Program Documentation and Behavior using Metamorphic LLM QueriesHyeonseok Lee, Gabin An, Shin Yoo. 120-127 [doi]
- CoCoNUT: Structural Code Understanding does not fall out of a treeClaas Beger, Saikat Dutta 0001. 128-136 [doi]
- From Theory to Practice: Code Generation Using LLMs for CAPEC and CWE FrameworksMurtuza Shahzad, Joseph Wilson, Ibrahim Al Azher, Hamed Alhoori, Mona Rahimi. 137-144 [doi]
- Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMsNilesh Dhulshette, Sapan Shah, Vinay Kulkarni 0001. 145-152 [doi]
- Code Summarization Beyond Function LevelVladimir Makharev, Vladimir Ivanov 0001. 153-160 [doi]
- Is More or Less Automation Better? An Investigation into the LLM4TDD ProcessSanyogita Piya, Anahita Samadi, Allison Sullivan. 161-168 [doi]
- Knowledge Graph Based Repository-Level Code GenerationMihir Athale, Vishal Vaddina. 169-176 [doi]
- Leveraging LLMs for Legacy Code Modernization: Evaluation of LLM-Generated DocumentationColin 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. 177-184 [doi]
- Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient PruningLaura Puccioni, Alireza Farshin, Mariano Scazzariello, Changjie Wang, Marco Chiesa, Dejan Kostic. 185-192 [doi]
- The Shortcomings of Code LLMs in Modeling Code PropertiesSrivishnu Pyda, Daniel Nichols, Abhinav Bhatele. 193-199 [doi]
- Mix-of-Language-Experts Architecture for Multilingual ProgrammingYifan Zong, Yuntian Deng, Pengyu Nie. 200-208 [doi]
- Do Code LLMs Understand Design Patterns?Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu 0001. 209-212 [doi]
- From Scientific Texts to Verifiable Code: Automating the Process with TransformersChangjie Wang, Mariano Scazzariello, Marco Chiesa. 213-216 [doi]