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ICSE 2021
Mon 17 May - Sat 5 June 2021

Software developers have heavily used online question and answer platforms to seek help to solve their technical problems. However, a major problem with these technical Q&A sites is \emph{“answer hungriness”} i.e., a large number of questions remain unanswered or unresolved, and users have to wait for a long time or painstakingly go through the provided answers with various levels of quality. To alleviate this time-consuming problem, we propose a novel {\sc DeepAns} neural network-based approach to identify the most relevant answer among a set of answer candidates. Our approach follows a three-stage process: question boosting, label establishment, and answer recommendation. Given a post, we first generate a clarifying question as a way of question boosting. We automatically establish the \emph{positive}, \emph{neutral$^+$}, \emph{neutral$^-$} and \emph{negative} training samples via label establishment. When it comes to answer recommendation, we sort answer candidates by the matching scores calculated by our neural network-based model. To evaluate the performance of our proposed model, we conducted a large scale evaluation on four datasets, collected from the real world technical Q&A sites (i.e., Ask Ubuntu, Super User, Stack Overflow Python and Stack Overflow Java). Our experimental results show that our approach significantly outperforms several state-of-the-art baselines in automatic evaluation. We also conducted a user study with 50 solved/unanswered/unresolved questions. The user study results demonstrate that our approach is effective in solving the answer hungry problem by recommending the most relevant answers from historical archives.

Thu 27 May

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

11:50 - 13:10
3.2.2. Q&A in Online Platforms: Stack Overflow #2 Journal-First Papers / Technical Track at Blended Sessions Room 2 +12h
Chair(s): Alexander Serebrenik Eindhoven University of Technology
11:50
20m
Paper
Technical Q&A Site Answer Recommendation via Question BoostingJournal-First
Journal-First Papers
Zhipeng Gao Monash University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, John Grundy Monash University
DOI Pre-print Media Attached
12:10
20m
Full-paper
Automated Query Reformulation for Efficient Search Based on Query Logs from Stack OverflowACM SIGSOFT Distinguished PaperTechnical Track
Technical Track
Kaibo Cao Software Institute, Nanjing University, Chunyang Chen Monash University, Sebastian Baltes QAware GmbH and The University of Adelaide, Christoph Treude University of Adelaide, Xiang Chen Nantong University
Pre-print Media Attached
12:30
20m
Paper
Automatic Solution Summarization for Crash BugsTechnical Track
Technical Track
Haoye Wang Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, John Grundy Monash University, Xinyu Wang Zhejiang University
Pre-print Media Attached
12:50
20m
Paper
Chatbot4QR: Interactive Query Refinement for Technical Question RetrievalJournal-First
Journal-First Papers
Neng Zhang Zhejiang University, China; PengCheng Laboratory, China, Qiao Huang Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, Ying Zou Queen's University, Kingston, Ontario, David Lo Singapore Management University, Zhenchang Xing Australian National University
DOI Pre-print Media Attached
23:50 - 01:10
3.2.2. Q&A in Online Platforms: Stack Overflow #2 Technical Track / Journal-First Papers at Blended Sessions Room 2
23:50
20m
Paper
Technical Q&A Site Answer Recommendation via Question BoostingJournal-First
Journal-First Papers
Zhipeng Gao Monash University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, John Grundy Monash University
DOI Pre-print Media Attached
00:10
20m
Full-paper
Automated Query Reformulation for Efficient Search Based on Query Logs from Stack OverflowACM SIGSOFT Distinguished PaperTechnical Track
Technical Track
Kaibo Cao Software Institute, Nanjing University, Chunyang Chen Monash University, Sebastian Baltes QAware GmbH and The University of Adelaide, Christoph Treude University of Adelaide, Xiang Chen Nantong University
Pre-print Media Attached
00:30
20m
Paper
Automatic Solution Summarization for Crash BugsTechnical Track
Technical Track
Haoye Wang Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, David Lo Singapore Management University, John Grundy Monash University, Xinyu Wang Zhejiang University
Pre-print Media Attached
00:50
20m
Paper
Chatbot4QR: Interactive Query Refinement for Technical Question RetrievalJournal-First
Journal-First Papers
Neng Zhang Zhejiang University, China; PengCheng Laboratory, China, Qiao Huang Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, Ying Zou Queen's University, Kingston, Ontario, David Lo Singapore Management University, Zhenchang Xing Australian National University
DOI Pre-print Media Attached