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ICSE 2021
Mon 17 May - Sat 5 June 2021

As a popular Q&A site for programming, Stack Overflow is a treasure for developers. However, the amount of questions and answers on Stack Overflow make it difficult for developers to efficiently locate the information they are looking for. There are two gaps leading to poor search results: the gap between the user’s intention and the textual query, and the semantic gap between the query and the post content. Therefore, developers have to constantly reformulate their queries by correcting misspelled words, adding limitations to certain programming languages or platforms, etc. As query reformulation is tedious for developers, especially for novices, we propose an automated software-specific query reformulation approach based on deep learning. With query logs provided by Stack Overflow, we construct a large-scale query reformulation corpus, including the original queries and corresponding reformulated ones. Our approach trains a Transformer model that can automatically generate candidate reformulated queries when given the user’s original query. The evaluation results show that our approach outperforms five state-of-the-art baselines, and achieves a 5.6% to 33.5% boost in terms of ExactMatch and a 4.8% to 14.4% boost in terms of GLEU.

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