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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.

Conference Day
Wed 8 Jul

Displayed time zone: (UTC) Coordinated Universal Time change

00:00 - 01:00
00:00
12m
Talk
PRECFIX: Large-Scale Patch Recommendation by Mining Defect-Patch PairsSEIP
Software Engineering in Practice
Xindong ZhangAlibaba Group, Chenguang ZhuUniversity of Texas, Austin, Yi LiNanyang Technological University, Jianmei GuoAlibaba Group, Lihua LiuAlibaba Group, Haobo GuAlibaba 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 LiuNanjing University of Aeronautics and Astronautics, Shangwen WangNational University of Defense Technology, Anil KoyuncuUniversity of Luxembourg, Luxembourg, Kisub KimUniversity of Luxembourg, SnT, Tegawendé F. BissyandéSnT, University of Luxembourg, Dongsun KimFuriosa.ai, Peng WuNational University of Defense Technology, Jacques KleinUniversity of Luxembourg, SnT, Xiaoguang MaoNational University of Defense Technology, Yves Le TraonUniversity of Luxembourg
Pre-print
00:24
8m
Talk
SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program RepairJ1
Journal First
Zimin ChenKTH Royal Institute of Technology, Steve KommruschColorado State University, Michele TufanoCollege of William and Mary, Louis-Noël PouchetColorado State University, USA, Denys PoshyvanykWilliam and Mary, Martin MonperrusKTH Royal Institute of Technology
00:32
8m
Talk
A Study of Bug Resolution Characteristics in Popular Programming LanguagesJ1
Journal First
Jie M. ZhangUniversity College London, UK, Feng Li, Dan HaoPeking University, Meng WangUniversity of Bristol, UK, Hao TangPeking University, Lu ZhangPeking University, China, Mark HarmanFacebook and University College London
00:40
12m
Talk
Automated Bug Reproduction from User Reviews for Android ApplicationsSEIP
Software Engineering in Practice
Shuyue LiXi'an Jiaotong University, Jiaqi GuoXi'an Jiaotong University, Ming FanXi'an Jiaotong University, Jian-Guang LouMicrosoft Research, Qinghua ZhengXi'an Jiaotong University, Ting LiuXi'an Jiaotong University
00:52
6m
Talk
CHASE: Checklist to Assess User Experience in Internet of Things EnvironmentsNIER
New Ideas and Emerging Results
Rodrigo AlmeidaFederal University of Ceará, Joseane PaivaFederal University of Ceará, Rossana AndradeFederal University of Ceará, Ticianne DarinFederal University of Ceará