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ORCID33rd ICPC 2025: Ottawa, ON, Canada
- 33rd IEEE/ACM International Conference on Program Comprehension, ICPC@ICSE 2025, Ottawa, ON, Canada, April 27-28, 2025. IEEE 2025, ISBN 979-8-3315-0223-2
- Jacob Trentini
, Victor Liu, Yiming Peng, Ziliang Zong:
Advancing Large Language Models in Code Generation: Usaco Benchmark and Bug Mitigation Insights. 1-12 - Gaia Colombo, Leonardo Mariani, Daniela Micucci, Oliviero Riganelli:
On the Possibility of Breaking Copyleft Licenses When Reusing Code Generated by ChatGPT. 1-12 - Federica Pepe, Claudia Farkas, Maleknaz Nayebi, Giuliano Antoniol, Massimiliano Di Penta:
How Do Papers Make Into Machine Learning Frameworks: a Preliminary Study on Tensorflow. 1-6 - Robert Husák, Jan Kofron, Filip Zavoral:
Combining Static Analysis Techniques for Program Comprehension Using Slicito. 1-5 - Junayed Mahmud, Antu Saha, Oscar Chaparro, Kevin Moran, Andrian Marcus:
Combining Language and App Ui Analysis for the Automated Assessment of Bug Reproduction Steps. 1-12 - Issam Sedki, Abdelwahab Hamou-Lhadj, Otmane Aït Mohamed, Naser Ezzati-Jivan:
Developing a Taxonomy for Advanced Log Parsing Techniques. 1-12 - Yifan Wu, Siyu Yu, Ying Li:
Log Parsing Using LLMs with Self-Generated In-Context Learning and Self-Correction. 1-12 - Barbara Russo, Jorge Melegati, Moritz Mock:
Leveraging Multi-Task Learning to Improve the Detection of SATD and Vulnerability. 1-12 - Hongkui He, Jiexin Wang, Liuwen Cao, Yi Cai:
CLCoSum: Curriculum Learning-Based Code Summarization for Code Language Models. 1-13 - Hui Li, Zhen Dong, Siao Wang, Hui Zhang, Liwei Shen, Xin Peng, Dongdong She:
Extracting Formal Specifications From Documents Using LLMS for Test Automation. 1-12 - Jueun Heo, Seonah Lee:
A Study on Applying Large Language Models to Issue Classification. 1-11 - Miki Yonekura, Yutaro Kashiwa, Bin Lin, Kenji Fujiwara, Hajimu Iida:
Leveraging Context Information for Self-Admitted Technical Debt Detection. 1-12 - Manish Acharya, Yifan Zhang, Kevin Leach, Yu Huang:
Optimizing Code Runtime Performance Through Context-Aware Retrieval-Augmented Generation. 1-5 - Markus Weninger, Simon Grünbacher, Herbert Prähofer:
JavaWiz: A Trace-Based Graphical Debugger for Software Development Education. 1-12 - Antonio Vitale, Emanuela Guglielmi, Rocco Oliveto, Simone Scalabrino:
Personalized Code Readability Assessment: Are We There Yet? 1-11 - Alessandro Midolo, Massimiliano Di Penta:
Automated Refactoring of Non-Idiomatic Python Code: A Differentiated Replication with LLMS. 1-11 - Wunan Guo, Zhen Dong, Liwei Shen, Daihong Zhou, Bin Hu, Chen Zhang, Hai Xue:
Effectively Modeling UI Transition Graphs for Android Apps Via Reinforcement Learning. 13-24 - Zixu Zhou, Rufeng Chen, Junfeng Chen, Yepang Liu, Lili Wei:
Characterizing Bugs in Login Processes of Android Applications: An Empirical Study. 25-36 - Minhong Dong, Liyuan Liu, Mengting Zhang, Sen Chen, Wenying He, Ze Wang, Yude Bai:
Calmdroid: Core-Set Based Active Learning for Multi-Label Android Malware Detection. 37-48 - Zaixing Zhang, Jianming Chang, Tianyuan Hu, Lulu Wang, Bixin Li:
Towards Task-Harmonious Vulnerability Assessment Based on LLM. 49-59 - Hakam W. Alomari, Christopher Vendome, Himal Gyawali:
A Slicing-Based Approach for Detecting and Patching Vulnerable Code Clones. 60-72 - Jiangnan Huang, Bin Lin:
Revisiting Security Practices for Github Actions Workflows. 73-77 - Shiyang Ye, Chao Ni, Jue Wang, Qianqian Pang, Xinrui Li, Xiaodan Xu:
Sembug: Detecting Logic Bugs in Dbms Through Generating Semantic-Aware Non-Optimizing Query. 124-135 - Sára Juhosová, Andy Zaidman, Jesper Cockx:
Pinpointing the Learning Obstacles of an Interactive Theorem Prover. 159-170 - Jayant Havare, Varsha Apte, Kaushikraj Maharajan, Nithin Chandra Gupta Samudrala, Ganesh Ramakrishnan, Srikanth Tamilselvam, Sainath Vavilapalli:
Ai-Based Automated Grading of Source Code of Introductory Programming Assignments. 171-181 - Anshul Shah, Thanh Tong, Elena Tomson, Steven Shi, William G. Griswold, Adalbert Gerald Soosai Raj:
Students' Program Comprehension Processes in a Large Code Base. 182-193 - Botond István Horváth, Richárd Szalay, Zoltán Porkoláb:
Overlord: A C++ Overloading Inspector. 194-198 - Federico Di Menna, Luca Traini, Gabriele Bavota, Vittorio Cortellessa:
Investigating Execution-Aware Language Models for Code Optimization. 204-215 - Maxime André, Marco Raglianti, Anthony Cleve, Michele Lanza:
Understanding Data Access in Microservices Applications Using Interactive Treemaps. 216-220 - Rémi Dufloer, Imen Sayar, Anne Etien, Steven Costiou:
Divergence-Driven Debugging: Understanding Behavioral Changes Between Two Program Versions. 221-225 - Feng Yang, Qi Xin, Zhilei Ren, Jifeng Xuan:
Kotsuite: Unit Test Generation for Kotlin Programs in Android Applications. 226-236 - Antonio Vitale, Antonio Mastropaolo, Rocco Oliveto, Massimiliano Di Penta, Simone Scalabrino:
Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough? 237-249 - Zhifang Liao, Xiaoyu Liu, Peng Lan, Song Yu, Pei Liu:
Cmdesum: A Cross-Modal Deliberation Network for Code Summarization. 250-261 - Zhiyang Zhang, Haiyang Yang, Qingyang Yan, Hao Yan, Weihuan Min, Zhao Wei, Li Kuang, Yingjie Xia:
DLCoG: A Novel Framework for Dual-Level Code Comment Generation Based on Semantic Segmentation and In-Context Learning. 275-285 - Pablo Valenzuela-Toledo, Chuyue Wu, Sandro Hernández, Alexander Boll, Roman Machácek, Sebastiano Panichella, Timo Kehrer:
Explaining GitHub Actions Failures with Large Language Models: Challenges, Insights, and Limitations. 286-297 - Kang Yang, Xinjun Mao, Shangwen Wang, Yanlin Wang, Tanghaoran Zhang, Bo Lin, Yihao Qin, Zhang Zhang, Yao Lu, Kamal Al-Sabahi:
Large Language Models Are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks. 298-309 - Natanael Djajadi, Amirhossein Deljouyi, Andy Zaidman:
Using Large Language Models to Generate Concise and Understandable Test Case Summaries. 322-326 - Francesco Casillo, Antonio Mastropaolo, Gabriele Bavota, Vincenzo Deufemia, Carmine Gravino:
Towards Generating the Rationale for Code Changes. 327-338 - Michael MacInnis, Olga Baysal, Michele Lanza:
Terminal Lucidity: Envisioning the Future of the Terminal. 339-349 - Alyssia Chen, Carol Wong, Bonita Sharif, Anthony Peruma:
Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists. 350-354 - Carol Wong, Gunnar Larsen, Rocky Huang, Bonita Sharif, Anthony Peruma:
Method Names in Jupyter Notebooks: An Exploratory Study. 355-366 - Christian D. Newman, Brandon Scholten, Sophia Testa, Joshua A. C. Behler, Syreen Banabilah, Michael L. Collard, Michael John Decker, Mohamed Wiem Mkaouer, Marcos Zampieri, Eman Abdullah AlOmar, Reem S. Alsuhaibani, Anthony Peruma, Jonathan I. Maletic:
Scalar: A Part-of-Speech Tagger for Identifiers. 367-371 - Alejandro Velasco, Aya Garryyeva, David N. Palacio, Antonio Mastropaolo, Denys Poshyvanyk:
Toward Neurosymbolic Program Comprehension. 377-381 - Robin van Straeten, Bin Lin:
Mining Code Change Patterns in Ada Projects. 387-397 - Carmen Armenti, Michele Lanza:
Telling Software Evolution Stories with Sonification. 398-402 - Baihui Sang, Liang Wang, Jierui Zhang, Xianping Tao:
Attributed Multiplex Learning for Analogical Third-Party Library Recommendation and Retrieval. 403-413 - Jahnavi Kumar, Siddhartha Gandu, Sridhar Chimalakonda:
LLM2FedLLM - A Tool for Simulating Federated LLMs for Software Engineering Tasks. 414-418 - Hailin Huang, Liuwen Cao, Jiexin Wang, Tianchen Yu, Yi Cai:
Code Ranking with Structure Awareness Contrastive Learning. 419-430 - Zhongyi Shi, Fuzhang Wu, Weibin Zeng, Yan Kong, Sicheng Shen, Yanjun Wu:
Algorithmic Inversion: A Learnable Algorithm Representation for Code Generation. 431-441 - Benedetta Donato, Leonardo Mariani, Daniela Micucci, Oliviero Riganelli:
Studying How Configurations Impact Code Generation in LLMs: The Case of ChatGPT. 442-453 - Cristina Improta, Rosalia Tufano, Pietro Liguori, Domenico Cotroneo, Gabriele Bavota:
Quality In, Quality Out: Investigating Training Data's Role in AI Code Generation. 454-465 - Alessandro Giagnorio, Alberto Martin-Lopez, Gabriele Bavota:
Enhancing Code Generation for Low-Resource Languages: No Silver Bullet. 478-488 - Weijia Li, Yongjie Qian, Ke Gao, Haixin Chen, Xinyu Wang, Yuchen Tong, Ling Li, Yanjun Wu, Chen Zhao:
Coft: Making Large Language Models Better Zero-Shot Learners for Code Generation. 489-499 - Wenwu Xu, Peng Wang, Haichao Shi, Guoqiao Zhou, Junliang Yao, Xiao-Yu Zhang:
GELog: a GPT-Enhanced Log Representation Method for Anomaly Detection. 524-535 - Zhengliang Li, Zhiwei Jiang, Qiguo Huang, Qing Gu:
LLM-BL: Large Language Models are Zero-Shot Rankers for Bug Localization. 548-559 - Asif Mohammed Samir, Mohammad Masudur Rahman:
Improved IR-Based Bug Localization with Intelligent Relevance Feedback. 560-571 - Shamima Yeasmin, Chanchal K. Roy, Kevin A. Schneider, Mohammad Masudur Rahman, Kartik Mittal, Ryder Hardy:
Towards Enhancing IR-Based Bug Localization Leveraging Texts and Multimedia from Bug Reports. 572-576 - Luqiao Wang, Qingshan Li, Di Cui, Mingkang Wang, Yutong Zhao, Yongye Xu, Huiying Zhuang, Yangtao Zhou, Lu Wang:
Building Bridges, Not Walls: Fairness-Aware and Accurate Recommendation of Code Reviewers via LLm-Based Agents Collaboration. 577-588 - Pavlína Wurzel Gonçalves, Pooja Rani, Margaret-Anne D. Storey, Diomidis Spinellis, Alberto Bacchelli:
Code Review Comprehension: Reviewing Strategies Seen Through Code Comprehension Theories. 589-601
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