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ICSE 2021
Mon 17 May - Sat 5 June 2021

This program is tentative and subject to change.

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.

This program is tentative and subject to change.

Thu 27 May
Times are displayed in 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 SerebrenikEindhoven University of Technology
11:50
20m
Paper
Technical Q&A Site Answer Recommendation via Question BoostingJournal-First
Journal-First Papers
zhipeng gaoMonash University, Xin XiaHuawei Software Engineering Application Technology Lab, David LoSingapore Management University, John GrundyMonash University
DOI Pre-print
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 CaoSoftware Institute, Nanjing University, Chunyang ChenMonash University, Sebastian BaltesQAware GmbH and The University of Adelaide, Christoph TreudeUniversity of Adelaide, Xiang ChenNantong University
Pre-print
12:30
20m
Paper
Automatic Solution Summarization for Crash BugsTechnical Track
Technical Track
Haoye WangZhejiang University, Xin XiaHuawei Software Engineering Application Technology Lab, David LoSingapore Management University, John GrundyMonash University, Xinyu WangZhejiang University
Pre-print
12:50
20m
Paper
Chatbot4QR: Interactive Query Refinement for Technical Question RetrievalJournal-First
Journal-First Papers
Neng ZhangZhejiang University, China; PengCheng Laboratory, China, Qiao HuangZhejiang University, Xin XiaHuawei Software Engineering Application Technology Lab, Ying ZouQueen's University, Kingston, Ontario, David LoSingapore Management University, Zhenchang XingAustralian National University
DOI Pre-print
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 gaoMonash University, Xin XiaHuawei Software Engineering Application Technology Lab, David LoSingapore Management University, John GrundyMonash University
DOI Pre-print
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 CaoSoftware Institute, Nanjing University, Chunyang ChenMonash University, Sebastian BaltesQAware GmbH and The University of Adelaide, Christoph TreudeUniversity of Adelaide, Xiang ChenNantong University
Pre-print
00:30
20m
Paper
Automatic Solution Summarization for Crash BugsTechnical Track
Technical Track
Haoye WangZhejiang University, Xin XiaHuawei Software Engineering Application Technology Lab, David LoSingapore Management University, John GrundyMonash University, Xinyu WangZhejiang University
Pre-print
00:50
20m
Paper
Chatbot4QR: Interactive Query Refinement for Technical Question RetrievalJournal-First
Journal-First Papers
Neng ZhangZhejiang University, China; PengCheng Laboratory, China, Qiao HuangZhejiang University, Xin XiaHuawei Software Engineering Application Technology Lab, Ying ZouQueen's University, Kingston, Ontario, David LoSingapore Management University, Zhenchang XingAustralian National University
DOI Pre-print
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