ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Wed 17 Apr 2024 14:00 - 14:15 at Amália Rodrigues - Evolution 1 Chair(s): Jonathan Sillito

Code comment generation aims at generating natural language descriptions for a code snippet to facilitate developers’ program comprehension activities. Despite being studied for a long time, a bottleneck for existing approaches is that given a code snippet, they can only generate one comment while developers usually need to know information from diverse perspectives such as what is the functionality of this code snippet and how to use it. To tackle this limitation, this study empirically investigates the feasibility of utilizing large language models (LLMs) to generate comments that can fulfill developers’ diverse intents. Our intuition is based on the facts that (1) the code and its pairwise comment are used during the pre-training process of LLMs to build the semantic connection between the natural language and programming language, and (2) comments in the real-world projects, which are collected for the pre-training, usually contain different developers’ intents. We thus postulate that the LLMs can already understand the code from different perspectives after the pre-training. Indeed, experiments on two large-scale datasets demonstrate the rationale of our insights: by adopting the in-context learning paradigm and giving adequate prompts to the LLM (\eg providing it with ten or more examples), the LLM can significantly outperform a state-of-the-art supervised learning approach on generating comments with multiple intents. Results also show that customized strategies for constructing the prompts and post-processing strategies for reranking the results can both boost the LLM’s performances, which shed light on future research directions for using LLMs to achieve comment generation.

Wed 17 Apr

Displayed time zone: Lisbon change

14:00 - 15:30
14:00
15m
Talk
Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning
Research Track
Mingyang Geng National University of Defense Technology, Shangwen Wang National University of Defense Technology, Dezun Dong NUDT, Haotian Wang National University of Defense Technolog, Ge Li Peking University, Zhi Jin Peking University, Xiaoguang Mao National University of Defense Technology, Liao Xiangke National University of Defense Technology
DOI Pre-print
14:15
15m
Talk
Block-based Programming for Two-Armed Robots: A Comparative Study
Research Track
Felipe Fronchetti Virginia Commonwealth University, Nico Ritschel University of British Columbia, Logan Schorr Virginia Commonwealth University, Chandler Barfield Virginia Commonwealth University, Gabriella Chang Virginia Commonwealth University, Rodrigo Spinola Virginia Commonwealth University, Reid Holmes University of British Columbia, David C. Shepherd Louisiana State University
DOI Pre-print Media Attached
14:30
15m
Talk
Exploiting Library Vulnerability via Migration Based Automating Test Generation
Research Track
Zirui Chen , Xing Hu Zhejiang University, Xin Xia Huawei Technologies, Yi Gao Zhejiang University, Tongtong Xu Huawei, David Lo Singapore Management University, Xiaohu Yang Zhejiang University
14:45
15m
Talk
ReposVul: A Repository-Level High-Quality Vulnerability Dataset
Industry Challenge Track
Xinchen Wang Harbin Institute of Technology, Ruida Hu Harbin Institute of Technology, Shenzhen, Cuiyun Gao Harbin Institute of Technology, Xin-Cheng Wen Harbin Institute of Technology, Yujia Chen Harbin Institute of Technology, Shenzhen, Qing Liao Harbin Institute of Technology
Pre-print File Attached
15:00
7m
Talk
JOG: Java JIT Peephole Optimizations and Tests from Patterns
Demonstrations
Zhiqiang Zang The University of Texas at Austin, Aditya Thimmaiah The University of Texas at Austin, Milos Gligoric The University of Texas at Austin
DOI Pre-print
15:07
7m
Talk
Predicting the Change Impact of Resolving Defects by Leveraging the Topics of Issue Reports in Open Source Software Systems
Journal-first Papers
Maram Assi Queen's University, Safwat Hassan University of Toronto, Canada, Stefanos Georgiou Queen's University, Ying Zou Queen's University, Kingston, Ontario
15:14
7m
Talk
Assessing the Exposure of Software Changes
Journal-first Papers
Mehran Meidani University of Waterloo, Maxime Lamothe Polytechnique Montreal, Shane McIntosh University of Waterloo
Link to publication Pre-print
15:21
7m
Talk
Responding to change over time: A longitudinal case study on changes in coordination mechanisms in large‑scale agile
Journal-first Papers
Marthe Berntzen University of Oslo, Viktoria Stray University of Oslo, Nils Brede Moe , Rashina Hoda Monash University