ICSE 2025 (series) / ICPC 2025 (series) / Replications and Negative Results (RENE) /
Towards Generating the Rationale for Code Changes
Sun 27 Apr 2025 17:16 - 17:22 at 205 - Summarisation, Natural Language Generation Chair(s): Oscar Chaparro, Coen De Roover, Gema Rodríguez-Pérez
Commit messages are essential to understand changes in software projects, providing a way for developers to communicate code evolution. Generating effective commit messages that explain the rationale behind changes is a challenging and time-consuming task. While previous research has shown success in automating straightforward commit messages (e.g., “add README”), our study explores a more complex task: generating rationale explanations for code changes. We developed a method to identify rationale sentences in commit messages and compiled a dataset of 45,945 commits with their corresponding rationales. A pre-trained model was trained on this dataset to generate rationale explanations. While the approach we engineered for the extraction of rationale from commit messages exhibited a 75% precision, the model trained to generate the rationale only worked in a minority of cases. Our findings highlight the difficulty of the tackled task and the need for additional research in the area. We release our dataset and code to foster the investigation of this problem.
Sun 27 AprDisplayed time zone: Eastern Time (US & Canada) change
Sun 27 Apr
Displayed time zone: Eastern Time (US & Canada) change
16:00 - 17:30 | Summarisation, Natural Language GenerationResearch Track / Early Research Achievements (ERA) / Replications and Negative Results (RENE) at 205 Chair(s): Oscar Chaparro William & Mary, Coen De Roover Vrije Universiteit Brussel, Gema Rodríguez-Pérez Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Okanagan Campus | ||
16:00 10mTalk | Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough? Research Track Antonio Vitale Politecnico di Torino, University of Molise, Antonio Mastropaolo William and Mary, USA, Rocco Oliveto University of Molise, Massimiliano Di Penta University of Sannio, Italy, Simone Scalabrino University of Molise | ||
16:10 10mTalk | CMDeSum: A Cross-Modal Deliberation Network for Code Summarization Research Track Zhifang Liao Central South University, Xiaoyu Liu Central South University, Peng Lan School of Computer Science and Engineering, Central South University, Changsha, China, Song Yu Central South University, Pei Liu Monash University | ||
16:20 10mTalk | CLCoSum: Curriculum Learning-based Code Summarization for Code Language Models Research Track Hongkui He South China University of Technology, Jiexin Wang South China University of Technology, Liuwen Cao South China University of Technology, Yi Cai School of Software Engineering, South China University of Technology, Guangzhou, China | ||
16:30 10mTalk | DLCoG: A Novel Framework for Dual-Level Code Comment Generation based on Semantic Segmentation and In-Context Learning Research Track Zhang Zhiyang , Haiyang Yang School of Computer Science and Engineering, Central South University, Qingyang Yan Central South University, Hao Yan Central South University, Wei-Huan Min Central South University, Zhao Wei Tencent, Li Kuang Central South University, Yingjie Xia Hangzhou Dianzi University | ||
16:40 10mTalk | Explaining GitHub Actions Failures with Large Language Models: Challenges, Insights, and Limitations Research Track Pablo Valenzuela-Toledo University of Bern, Universidad de La Frontera, Chuyue Wu University of Bern, Sandro Hernández University of Bern, Alexander Boll University of Bern, Roman Machacek University of Bern, Sebastiano Panichella University of Bern, Timo Kehrer University of Bern | ||
16:50 10mTalk | Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks Research Track Kang Yang National University of Defense Technology, Xinjun Mao National University of Defense Technology, Shangwen Wang National University of Defense Technology, Yanlin Wang Sun Yat-sen University, Tanghaoran Zhang National University of Defense Technology, Yihao Qin National University of Defense Technology, Bo Lin National University of Defense Technology, Zhang Zhang Key Laboratory of Software Engineering for Complex Systems, National University of Defense Technology, Yao Lu National University of Defense Technology, Kamal Al-Sabahi College of Banking and Financial Studies Pre-print | ||
17:00 10mTalk | Extracting Formal Specifications from Documents Using LLMs for Test Automation Research Track Hui Li Xiamen University, Zhen Dong Fudan University, Siao Wang Fudan University, Hui Zhang Fudan University, Liwei Shen Fudan University, Xin Peng Fudan University, Dongdong She HKUST (The Hong Kong University of Science and Technology) | ||
17:10 6mTalk | Using Large Language Models to Generate Concise and Understandable Test Case Summaries Early Research Achievements (ERA) Natanael Djajadi Delft University of Technology, Amirhossein Deljouyi Delft University of Technology, Andy Zaidman TU Delft Pre-print | ||
17:16 6mTalk | Towards Generating the Rationale for Code Changes Replications and Negative Results (RENE) Francesco Casillo Università di Salerno, Antonio Mastropaolo William and Mary, USA, Gabriele Bavota Software Institute @ Università della Svizzera Italiana, Vincenzo Deufemia University of Salerno, Carmine Gravino University of Salerno | ||
17:22 8mTalk | Session's Discussion: "Summarisation, Natural Language Generation" Research Track | ||