Practitioners’ Expectations on Automated Code Comment Generation
Wed 11 May 2022 21:10 - 21:15 at ICSE room 1-odd hours - Program Comprehension 3 Chair(s): Christina von Flach
Good comments are invaluable assets to software projects, as they help developers understand and maintain projects. However, due to some poor commenting practices, comments are often missing or inconsistent with the source code. Software engineering practitioners often spend a significant amount of time and effort reading and understanding programs without or with poor comments. To counter this, researchers have proposed various techniques to automatically generate code comments in recent years, which can not only save developers time writing comments but also help them better understand existing software projects. However, it is unclear whether these techniques can alleviate comment issues and whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by interviewing and surveying practitioners about their expectations of research in code comment generation. We then compared what practitioners need and the current state-of-the-art research by performing a literature review of papers on code comment generation techniques published in the premier publication venues from 2010 to 2020. From this comparison, we highlighted the directions where researchers need to put effort to develop comment generation techniques that matter to practitioners.
Wed 11 MayDisplayed time zone: Eastern Time (US & Canada) change
05:00 - 06:00 | Program Comprehension 1Technical Track / NIER - New Ideas and Emerging Results at ICSE room 2-odd hours Chair(s): Prajish Prasad IIT Bombay | ||
05:00 5mTalk | Supporting program comprehension by generating abstract code summary tree NIER - New Ideas and Emerging Results Avijit Bhattacharjee University of Saskatchewan, Canada, Banani Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan DOI Pre-print Media Attached | ||
05:05 5mTalk | Practitioners’ Expectations on Automated Code Comment Generation Technical Track Xing Hu Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, Zhiyuan Wan Zhejiang University, Qiuyuan Chen Zhejiang University, Thomas Zimmermann Microsoft Research DOI Pre-print Media Attached | ||
05:10 5mTalk | On the Evaluation of Neural Code Summarization Technical Track Ensheng Shi Xi'an Jiaotong University, Yanlin Wang Microsoft Research, Lun Du Microsoft Research Asia, Junjie Chen Tianjin University, Shi Han Microsoft Research, Hongyu Zhang University of Newcastle, Dongmei Zhang Microsoft Research, Hongbin Sun Xi'an Jiaotong University DOI Pre-print Media Attached | ||
05:15 5mTalk | Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding Technical Track Deze Wang National University of Defense Technology, Zhouyang Jia National University of Defense Technology, Shanshan Li National University of Defense Technology, Yue Yu College of Computer, National University of Defense Technology, Changsha 410073, China, Yun Xiong Fudan University, Wei Dong School of Computer, National University of Defense Technology, China, Liao Xiangke National University of Defense Technology Pre-print Media Attached | ||
05:20 5mTalk | FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation Technical Track Jinhao Dong Peking University, Yiling Lou Purdue University, Qihao Zhu Peking University, Zeyu Sun Peking University, Zhilin Li Peking University, Wenjie Zhang Peking University, Dan Hao Peking University Pre-print Media Attached | ||
21:00 - 22:00 | Program Comprehension 3Technical Track / SEET - Software Engineering Education and Training / NIER - New Ideas and Emerging Results at ICSE room 1-odd hours Chair(s): Christina von Flach Federal University of Bahia | ||
21:00 5mTalk | Supporting program comprehension by generating abstract code summary tree NIER - New Ideas and Emerging Results Avijit Bhattacharjee University of Saskatchewan, Canada, Banani Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan DOI Pre-print Media Attached | ||
21:05 5mTalk | Designing Divergent Thinking, Creative Problem Solving Exams SEET - Software Engineering Education and Training Pre-print Media Attached | ||
21:10 5mTalk | Practitioners’ Expectations on Automated Code Comment Generation Technical Track Xing Hu Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, Zhiyuan Wan Zhejiang University, Qiuyuan Chen Zhejiang University, Thomas Zimmermann Microsoft Research DOI Pre-print Media Attached | ||
21:15 5mTalk | Retrieving Data Constraint Implementations Using Fine-Grained Code Patterns Technical Track Juan Manuel Florez The University of Texas at Dallas, Jonathan Perry The University of Texas at Dallas, Shiyi Wei University of Texas at Dallas, Andrian Marcus University of Texas at Dallas Pre-print Media Attached | ||
21:20 5mTalk | Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding Technical Track Deze Wang National University of Defense Technology, Zhouyang Jia National University of Defense Technology, Shanshan Li National University of Defense Technology, Yue Yu College of Computer, National University of Defense Technology, Changsha 410073, China, Yun Xiong Fudan University, Wei Dong School of Computer, National University of Defense Technology, China, Liao Xiangke National University of Defense Technology Pre-print Media Attached | ||