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ICSE 2020
Wed 24 June - Thu 16 July 2020
Wed 8 Jul 2020 00:32 - 00:40 at Silla - P9-Bugs and Repair Chair(s): Yingfei Xiong

This paper presents a large-scale study that investigates the bug resolution characteristics among popular Github projects written in different programming languages. We explore correlations but, of course, we cannot infer causation. Specifically, we analyse bug resolution data from approximately 70 million Source Line of Code, drawn from 3 million commits to 600 GitHub projects, primarily written in 10 programming languages. We find notable variations in apparent bug resolution time and patch (fix) size. While interpretation of results from such large-scale empirical studies is inherently difficult, we believe that the differences in medians are sufficiently large to warrant further investigation, replication, re-analysis and follow up research. For example, in our corpus, the median apparent bug resolution time (elapsed time from raise to resolve) for Ruby was 4X that for Go and 2.5X for Java. We also found that patches tend to touch more files for the corpus of strongly typed and for statically typed programs. However, we also found evidence for a lower elapsed resolution time for bug resolution committed to projects constructed from statically typed languages. These findings, if replicated in subsequent follow on studies, may shed further empirical light on the debate about the importance of static typing.

Wed 8 Jul

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00:00 - 01:00
00:00
12m
Talk
PRECFIX: Large-Scale Patch Recommendation by Mining Defect-Patch PairsSEIP
Software Engineering in Practice
Xindong Zhang Alibaba Group, Chenguang Zhu University of Texas, Austin, Yi Li Nanyang Technological University, Jianmei Guo Alibaba Group, Lihua Liu Alibaba Group, Haobo Gu Alibaba Group
Pre-print
00:12
12m
Talk
On the Efficiency of Test Suite based Program Repair: A Systematic Assessment of 16 Automated Repair Systems for Java ProgramsArtifact ReusableTechnicalArtifact Available
Technical Papers
Kui Liu Nanjing University of Aeronautics and Astronautics, Shangwen Wang National University of Defense Technology, Anil Koyuncu University of Luxembourg, Luxembourg, Kisub Kim University of Luxembourg, SnT, Tegawendé F. Bissyandé SnT, University of Luxembourg, Dongsun Kim Furiosa.ai, Peng Wu National University of Defense Technology, Jacques Klein University of Luxembourg, SnT, Xiaoguang Mao National University of Defense Technology, Yves Le Traon University of Luxembourg
Pre-print
00:24
8m
Talk
SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program RepairJ1
Journal First
Zimin Chen KTH Royal Institute of Technology, Steve Kommrusch Colorado State University, Michele Tufano College of William and Mary, Louis-Noël Pouchet Colorado State University, USA, Denys Poshyvanyk William and Mary, Martin Monperrus KTH Royal Institute of Technology
00:32
8m
Talk
A Study of Bug Resolution Characteristics in Popular Programming LanguagesJ1
Journal First
Jie M. Zhang University College London, UK, Feng Li , Dan Hao Peking University, Meng Wang University of Bristol, UK, Hao Tang Peking University, Lu Zhang Peking University, China, Mark Harman Facebook and University College London
00:40
12m
Talk
Automated Bug Reproduction from User Reviews for Android ApplicationsSEIP
Software Engineering in Practice
Shuyue Li Xi'an Jiaotong University, Jiaqi Guo Xi'an Jiaotong University, Ming Fan Xi'an Jiaotong University, Jian-Guang Lou Microsoft Research, Qinghua Zheng Xi'an Jiaotong University, Ting Liu Xi'an Jiaotong University
00:52
6m
Talk
CHASE: Checklist to Assess User Experience in Internet of Things EnvironmentsNIER
New Ideas and Emerging Results
Rodrigo Almeida Federal University of Ceará, Joseane Paiva Federal University of Ceará, Rossana Andrade Federal University of Ceará, Ticianne Darin Federal University of Ceará