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ICSE 2021
Mon 17 May - Sat 5 June 2021

Virtual conversational assistants designed specifically for software engineers could have a huge impact on the time it takes for software engineers to get help. Research efforts are focusing on virtual assistants that support specific software development tasks such as bug repair and pair programming. In this paper, we study the use of online chat platforms as a resource towards collecting developer opinions that could potentially help in building opinion Q&A systems, as a specialized instance of virtual assistants and chatbots for software engineers. Opinion Q&A has a stronger presence in chats than in other developer communications, thus mining them can provide a valuable resource for developers in quickly getting insight about a specific development topic (e.g., What is the best Java library for parsing JSON?). We address the problem of opinion Q&A extraction by developing automatic identification of opinion-asking questions and extraction of participants’ answers from public online developer chats. We evaluate our automatic approaches on chats spanning six programming communities and two platforms. Our results show that a heuristic approach to opinion-asking questions works well (.87 precision), and a deep learning approach customized to the software domain outperforms heuristics-based, machine-learning-based and deep learning for answer extraction in community question answering.

Wed 26 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

20:40 - 21:40
2.6.2. Q&A in Online Platforms: Stack Overflow #1Journal-First Papers / Technical Track at Blended Sessions Room 2 +12h
Chair(s): Francisco Servant Virginia Tech
20:40
20m
Paper
Reading Answers on Stack Overflow: Not Enough!Journal-First
Journal-First Papers
Haoxiang Zhang Centre for Software Excellence, Huawei, Canada, Shaowei Wang University of Manitoba, Tse-Hsun (Peter) Chen Concordia University, Ahmed E. Hassan School of Computing, Queen's University
Pre-print Media Attached
21:00
20m
Paper
An Empirical Study of Developer Discussions in the Gitter PlatformJournal-First
Journal-First Papers
Osama Ehsan Queen's University, Canada, Safwat Hassan Thompson Rivers University, Mariam El Mezouar Royal Military College, Ying Zou Queen's University, Kingston, Ontario
Pre-print Media Attached
21:20
20m
Paper
Automatic Extraction of Opinion-based Q&A from Online Developer ChatsTechnical Track
Technical Track
Preetha Chatterjee University of Delaware, Kostadin Damevski Virginia Commonwealth University, Lori Pollock University of Delaware
Pre-print Media Attached

Thu 27 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

08:40 - 09:40
2.6.2. Q&A in Online Platforms: Stack Overflow #1Journal-First Papers / Technical Track at Blended Sessions Room 2
08:40
20m
Paper
Reading Answers on Stack Overflow: Not Enough!Journal-First
Journal-First Papers
Haoxiang Zhang Centre for Software Excellence, Huawei, Canada, Shaowei Wang University of Manitoba, Tse-Hsun (Peter) Chen Concordia University, Ahmed E. Hassan School of Computing, Queen's University
Pre-print Media Attached
09:00
20m
Paper
An Empirical Study of Developer Discussions in the Gitter PlatformJournal-First
Journal-First Papers
Osama Ehsan Queen's University, Canada, Safwat Hassan Thompson Rivers University, Mariam El Mezouar Royal Military College, Ying Zou Queen's University, Kingston, Ontario
Pre-print Media Attached
09:20
20m
Paper
Automatic Extraction of Opinion-based Q&A from Online Developer ChatsTechnical Track
Technical Track
Preetha Chatterjee University of Delaware, Kostadin Damevski Virginia Commonwealth University, Lori Pollock University of Delaware
Pre-print Media Attached