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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021

The International Conference on Mining Software Repositories (MSR) has hosted a mining challenge since 2006. With this challenge, we call upon everyone interested to apply their tools to a common dataset. The challenge is for researchers and practitioners to bravely use their mining tools and approaches on a dare.

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Mon 17 May

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

03:10 - 04:00
Welcome Event Technical Papers / Tutorials / MIP Award / FOSS Award / content / Mining Challenge / Hackathon / MSR Awards / Registered Reports / Data Showcase / Shadow PC / Keynotes at MSR Room 1

The MSR welcoming sessions will feature informal networking opportunities for newcomers to meet each other, learn about the MSR conference series, and interact with some established MSR veterans. All are welcome!

10:00 - 10:50
Resources for MSR ResearchTechnical Papers / Data Showcase at MSR Room 1
Chair(s): Felipe Ebert Eindhoven University of Technology
10:01
3m
Talk
PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code
Technical Papers
Egor Spirin JetBrains Research; National Research University Higher School of Economics, Egor Bogomolov JetBrains Research, Vladimir Kovalenko JetBrains Research, Timofey Bryksin JetBrains Research, Saint Petersburg State University
Pre-print
10:04
3m
Talk
Mining DEV for social and technical insights about software development
Technical Papers
Maria Papoutsoglou Aristotle University of Thessaloniki, Johannes Wachs Vienna University of Economics and Business & Complexity Science Hub Vienna, Georgia Kapitsaki University of Cyprus
Pre-print
10:07
3m
Talk
TNM: A Tool for Mining of Socio-Technical Data from Git Repositories
Technical Papers
Nikolai Sviridov ITMO University, Mikhail Evtikhiev JetBrains Research, Vladimir Kovalenko JetBrains Research
Pre-print
10:10
3m
Talk
Identifying Versions of Libraries used in Stack Overflow Code Snippets
Technical Papers
Ahmed Zerouali Vrije Universiteit Brussel, Camilo Velázquez-Rodríguez Vrije Universiteit Brussel, Coen De Roover Vrije Universiteit Brussel
Pre-print Media Attached
10:13
3m
Talk
Sampling Projects in GitHub for MSR Studies
Data Showcase
Ozren Dabic Software Institute, Università della Svizzera italiana (USI), Switzerland, Emad Aghajani Software Institute, USI Università della Svizzera italiana, Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print
10:16
3m
Talk
gambit – An Open Source Name Disambiguation Tool for Version Control Systems
Technical Papers
Christoph Gote Chair of Systems Design, ETH Zurich, Christian Zingg Chair of Systems Design, ETH Zurich
Pre-print Media Attached
10:19
31m
Live Q&A
Discussions and Q&A
Technical Papers

10:00 - 10:50
Testing and code reviewTechnical Papers / Data Showcase / Registered Reports at MSR Room 2
Chair(s): Jürgen Cito TU Wien and Facebook
10:01
3m
Talk
A Traceability Dataset for Open Source Systems
Data Showcase
Mouna Hammoudi JOHANNES KEPLER UNIVERSITY LINZ, Christoph Mayr-Dorn Johannes Kepler University, Linz, Atif Mashkoor Johannes Kepler University Linz, Alexander Egyed Johannes Kepler University
Media Attached
10:04
4m
Talk
How Java Programmers Test Exceptional Behavior
Technical Papers
Diego Marcilio USI Università della Svizzera italiana, Carlo A. Furia Università della Svizzera italiana (USI)
Pre-print
10:08
4m
Talk
An Exploratory Study of Log Placement Recommendation in an Enterprise System
Technical Papers
Jeanderson Cândido Delft University of Technology, Jan Haesen Adyen N.V., Maurício Aniche Delft University of Technology, Arie van Deursen Delft University of Technology, Netherlands
Pre-print Media Attached
10:12
3m
Talk
Does Code Review Promote Conformance? A Study of OpenStack Patches
Technical Papers
Panyawut Sri-iesaranusorn Nara Institute of Science and Technology, Raula Gaikovina Kula NAIST, Takashi Ishio Nara Institute of Science and Technology
Pre-print
10:15
4m
Talk
A Replication Study on the Usability of Code Vocabulary in Predicting Flaky Tests
Technical Papers
Guillaume Haben University of Luxembourg, Sarra Habchi University of Luxembourg, Luxembourg, Mike Papadakis University of Luxembourg, Luxembourg, Maxime Cordy University of Luxembourg, Luxembourg, Yves Le Traon University of Luxembourg, Luxembourg
Pre-print Media Attached
10:19
3m
Talk
On the Use of Mutation in Injecting Test Order-Dependency
Registered Reports
Sarra Habchi University of Luxembourg, Luxembourg, Maxime Cordy University of Luxembourg, Luxembourg, Mike Papadakis University of Luxembourg, Luxembourg, Yves Le Traon University of Luxembourg, Luxembourg
Pre-print Media Attached
10:22
28m
Live Q&A
Discussions and Q&A
Technical Papers

11:10 - 12:00
Welcome Event Technical Papers / Tutorials / MIP Award / FOSS Award / content / Mining Challenge / Hackathon / MSR Awards / Registered Reports / Data Showcase / Shadow PC / Keynotes at MSR Room 1

The MSR welcoming sessions will feature informal networking opportunities for newcomers to meet each other, learn about the MSR conference series, and interact with some established MSR veterans. All are welcome!

17:00 - 17:50
Mining Challenge SessionMining Challenge / Technical Papers at MSR Room 1
Chair(s): Miltiadis Allamanis Microsoft Research, UK, Rafael-Michael Karampatsis The University of Edinburgh, Charles Sutton Google Research
17:01
2m
Welcome by the Mining Challenge Co-chairs
Mining Challenge
Miltiadis Allamanis Microsoft Research, UK, Rafael-Michael Karampatsis The University of Edinburgh, Charles Sutton Google Research
17:03
3m
Talk
A large-scale study on human-cloned changes for automated program repair
Mining Challenge
Fernanda Madeiral KTH Royal Institute of Technology, Thomas Durieux KTH Royal Institute of Technology, Sweden
Link to publication Pre-print
17:06
3m
Talk
Applying CodeBERT for Automated Program Repair of Java Simple Bugs
Mining Challenge
Ehsan Mashhadi University of Calgary, Hadi Hemmati University of Calgary
Pre-print Media Attached
17:09
3m
Talk
PySStuBs: Characterizing Single-Statement Bugs in Popular Open-Source Python Projects
Mining Challenge
Arthur Veloso Kamienski University of Alberta, Luisa Palechor University of Alberta, Abram Hindle University of Alberta, Cor-Paul Bezemer University of Alberta
Pre-print
17:12
3m
Talk
How Effective is Continuous Integration in Indicating Single-Statement Bugs?
Mining Challenge
Jasmine Latendresse Concordia University, Rabe Abdalkareem Queens University, Kingston, Canada, Diego Costa Concordia University, Canada, Emad Shihab Concordia University
Pre-print
17:15
3m
Talk
Mea culpa: How developers fix their own simple bugs differently from other developers
Mining Challenge
Wenhan Zhu University of Waterloo, Michael W. Godfrey University of Waterloo, Canada
Pre-print
17:18
3m
Talk
On the Distribution of "Simple Stupid Bugs" in Unit Test Files: An Exploratory Study
Mining Challenge
Anthony Peruma Rochester Institute of Technology, Christian D. Newman Rochester Institute of Technology
Pre-print Media Attached
17:21
3m
Talk
On the Rise and Fall of Simple Stupid Bugs: a Life-Cycle Analysis of SStuBs
Mining Challenge
Balázs Mosolygó University of Szeged, Norbert Vándor University of Szeged, Gabor Antal University of Szeged, Peter Hegedus University of Szeged
Pre-print
17:24
3m
Talk
On the Effectiveness of Deep Vulnerability Detectors to Simple Stupid Bug Detection
Mining Challenge
Jiayi Hua Beijing University of Posts and Telecommunications, Haoyu Wang Beijing University of Posts and Telecommunications
Pre-print
17:27
23m
Live Q&A
Discussions and Q&A
Technical Papers

18:10 - 19:00
Keynote: Nicole Forsgren Technical Papers at MSR Room 1

Tue 18 May

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

02:00 - 02:50
Keynote: Leslie MileyTechnical Papers at MSR Room 1
03:10 - 04:00
Technical Debt and SmellsTechnical Papers / Data Showcase at MSR Room 1
Chair(s): Gema Rodríguez-Pérez University of Waterloo
03:11
4m
Talk
Technical Debt in the Peer-Review Documentation of R Packages: a rOpenSci Case Study
Technical Papers
Zadia Codabux University of Saskatchewan, Melina Vidoni RMIT University, Fatemeh Hendijani Fard University of British Columbia
Pre-print
03:15
3m
Talk
QScored: A Large Dataset of Code Smells and Quality Metrics
Data Showcase
Tushar Sharma Siemens Research, Marouane Kessentini University of Michigan
Pre-print
03:18
3m
Talk
Architecture Smells and Pareto Principle: A Preliminary Empirical Exploration
Technical Papers
Pre-print
03:21
4m
Talk
Self-Admitted Technical Debt in R Packages: An Exploratory Study
Technical Papers
Melina Vidoni RMIT University
Pre-print
03:25
4m
Full-paper
An Empirical Study of Developer Discussions on Low Code Software Development Challenges
Technical Papers
Md Abdullah Al Alamin University of Calgary, Sanjay Malakar Bangladesh University of Engineering and Technology, Gias Uddin University of Calgary, Canada, Sadia Afroz Bangladesh University of Engineering and Technology, Tameem Bin Haider Bangladesh University of Engineering and Technology, Anindya Iqbal Bangladesh University of Engineering and Technology Dhaka, Bangladesh
Pre-print
03:29
31m
Live Q&A
Discussions and Q&A
Technical Papers

03:10 - 04:00
Time series dataData Showcase / Technical Papers at MSR Room 2
Chair(s): Shane McIntosh University of Waterloo
03:11
3m
Talk
AndroCT: Ten Years of App Call Traces in Android
Data Showcase
Wen Li , Xiaoqin Fu Washington State University, Haipeng Cai Washington State University, USA
Pre-print Media Attached
03:14
4m
Talk
Mining Workflows for Anomalous Data Transfers
Technical Papers
Huy Tu North Carolina State University, USA, George Papadimitriou University of Southern California, Mariam Kiran ESnet, LBNL, Cong Wang Renaissance Computing Institute, Anirban Mandal Renaissance Computing Institute, Ewa Deelman University of Southern California, Tim Menzies North Carolina State University, USA
Pre-print
03:18
4m
Talk
Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git Data
Technical Papers
Samuel W. Flint University of Nebraska-Lincoln, Jigyasa Chauhan University of Nebraska-Lincoln, Robert Dyer University of Nebraska-Lincoln
Pre-print Media Attached
03:22
4m
Paper
On the Naturalness and Localness of Software Logs
Technical Papers
Sina Gholamian University of Waterloo, Paul A. S. Ward University of Waterloo
Pre-print
03:26
4m
Talk
How Do Software Developers Use GitHub Actions to Automate Their Workflows?
Technical Papers
Timothy Kinsman University of Adelaide, Mairieli Wessel University of Sao Paulo, Marco Gerosa Northern Arizona University, USA, Christoph Treude University of Adelaide
Pre-print
03:30
30m
Live Q&A
Discussions and Q&A
Technical Papers

10:00 - 10:50
Developer communicationsTechnical Papers / Data Showcase at MSR Room 1
Chair(s): Hourieh Khalajzadeh Monash University, Australia
10:01
3m
Talk
Waiting around or job half-done? Sentiment in self-admitted technical debt
Technical Papers
Gianmarco Fucci University of Sannio, Nathan Cassee Eindhoven University of Technology, Fiorella Zampetti University of Sannio, Italy, Nicole Novielli University of Bari, Alexander Serebrenik Eindhoven University of Technology, Massimiliano Di Penta University of Sannio, Italy
Pre-print Media Attached
10:04
4m
Research paper
Automatically Selecting Follow-up Questions for Deficient Bug Reports
Technical Papers
Mia Mohammad Imran Virginia Commonwealth University, Agnieszka Ciborowska Virginia Commonwealth University, Kostadin Damevski Virginia Commonwealth University
Pre-print
10:08
4m
Talk
Challenges in Developing Desktop Web Apps: a Study of Stack Overflow and GitHub
Technical Papers
Gian Luca Scoccia University of L'Aquila, Patrizio Migliarini DISIM, University of L'Aquila, Marco Autili University of L'Aquila, Italy
Pre-print
10:12
3m
Talk
Search4Code: Code Search Intent Classification Using Weak Supervision
Data Showcase
Nikitha Rao Microsoft Research, Chetan Bansal Microsoft Research, Joe Guan Microsoft
Pre-print
10:15
35m
Live Q&A
Discussions and Q&A
Technical Papers

10:00 - 10:50
ML and Deep LearningTechnical Papers / Data Showcase / Registered Reports at MSR Room 2
Chair(s): Hongyu Zhang The University of Newcastle
10:01
4m
Talk
Fast and Memory-Efficient Neural Code Completion
Technical Papers
Alexey Svyatkovskiy Microsoft, Sebastian Lee University of Oxford, Anna Hadjitofi Alan Turing Institute, Maik Riechert Microsoft Research, Juliana Vicente Franco Microsoft Research, Miltiadis Allamanis Microsoft Research, UK
Pre-print Media Attached
10:05
4m
Research paper
Comparative Study of Feature Reduction Techniques in Software Change Prediction
Technical Papers
Ruchika Malhotra Delhi Technological University, Ritvik Kapoor Delhi Technological University, Deepti Aggarwal Delhi Technological University, Priya Garg Delhi Technological University
Pre-print
10:09
4m
Talk
An Empirical Study on the Usage of BERT Models for Code Completion
Technical Papers
Matteo Ciniselli Università della Svizzera Italiana, Nathan Cooper William & Mary, Luca Pascarella Università della Svizzera italiana (USI), Denys Poshyvanyk College of William & Mary, Massimiliano Di Penta University of Sannio, Italy, Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print
10:13
3m
Talk
ManyTypes4Py: A benchmark Python dataset for machine learning-based type inference
Data Showcase
Amir Mir Delft University of Technology, Evaldas Latoskinas Delft University of Technology, Georgios Gousios Facebook & Delft University of Technology
Pre-print
10:16
3m
Talk
KGTorrent: A Dataset of Python Jupyter Notebooks from Kaggle
Data Showcase
Luigi Quaranta University of Bari, Italy, Fabio Calefato University of Bari, Filippo Lanubile University of Bari
10:19
3m
Talk
Exploring the relationship between performance metrics and cost saving potential of defect prediction models
Registered Reports
Steffen Herbold University of Göttingen
Pre-print
10:22
28m
Live Q&A
Discussions and Q&A
Technical Papers

11:10 - 12:00
11:10
50m
Tutorial
PyDriller 1.0 -- Ready to grow together
Tutorials
Alberto Bacchelli University of Zurich, Maurício Aniche Delft University of Technology
Pre-print
17:00 - 17:50
HackathonTechnical Papers / Hackathon at MSR Room 1
Chair(s): Jim Herbsleb Carnegie Mellon University, Audris Mockus The University of Tennessee, Alexander Nolte University of Tartu
17:01
2m
Welcome by the MSR Hackathon Co-Chairs
Hackathon
Jim Herbsleb Carnegie Mellon University, Audris Mockus The University of Tennessee, Alexander Nolte University of Tartu
17:03
3m
Talk
An Exploratory Study of Project Activity Changepoints in Open Source Software Evolution
Hackathon
James Walden Northern Kentucky University, Noah Burgin, Kuljit Kaur Chahal Kaur
17:06
3m
Paper
The Diversity-Innovation Paradox in Open-Source Software
Hackathon
Mengchen Sam Yong Carnegie Mellon University, Pittsburgh, Pennsylvania, United States, Lavinia Francesca Paganini Federal University of Pernambuco, Huilian Sophie Qiu Carnegie Mellon University, Pittsburgh, Pennsylvania, United States, José Bayoán Santiago Calderón University of Virginia, USA
DOI Pre-print
17:09
4m
Talk
The Secret Life of Hackathon Code
Technical Papers
Ahmed Samir Imam Mahmoud University of Tartu, Tapajit Dey Lero - The Irish Software Research Centre and University of Limerick, Alexander Nolte University of Tartu, Audris Mockus The University of Tennessee, Jim Herbsleb Carnegie Mellon University
Pre-print
17:13
3m
Talk
Tracing Vulnerable Code Lineage
Hackathon
David Reid University of Tennessee, Kalvin Eng University of Alberta, Chris Bogart Carnegie Mellon University, Adam Tutko University of Tennessee - Knoxville
Pre-print
17:16
3m
Talk
Building the Collaboration Graph of Open-Source Software Ecosystem
Hackathon
Elena Lyulina JetBrains Research, Mahmoud Jahanshahi
Pre-print
17:19
1m
Talk
The Secret Life of Hackathon Code
Hackathon
Ahmed Samir Imam Mahmoud University of Tartu, Tapajit Dey Lero - The Irish Software Research Centre and University of Limerick
Pre-print
17:20
30m
Live Q&A
Discussions and Q&A
Technical Papers

17:00 - 17:50
TestingTechnical Papers / Data Showcase at MSR Room 2
Chair(s): Abram Hindle University of Alberta
17:01
4m
Talk
What Code Is Deliberately Excluded from Test Coverage and Why?
Technical Papers
Pre-print
17:05
3m
Talk
AndroR2: A Dataset of Manually-Reproduced Bug Reports for Android apps
Data Showcase
Tyler Wendland University of Minnesota, Jingyang Sun University of Bristish Columbia, Junayed Mahmud George Mason University, S M Hasan Mansur George Mason University, Steven Huang University of Bristish Columbia, Kevin Moran George Mason University, Julia Rubin University of British Columbia, Canada, Mattia Fazzini University of Minnesota
17:08
3m
Talk
Apache Software Foundation Incubator Project Sustainability Dataset
Data Showcase
Likang Yin University of California, Davis, Zhiyuan Zhang University of California, Davis, Qi Xuan Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou 310023, China, Vladimir Filkov University of California at Davis, USA
17:11
4m
Talk
Leveraging Models to Reduce Test Cases in Software Repositories
Technical Papers
Golnaz Gharachorlu Simon Fraser University, Nick Sumner Simon Fraser University
Pre-print Media Attached
17:15
4m
Talk
Which contributions count? Analysis of attribution in open source
Technical Papers
Jean-Gabriel Young University of Vermont, Amanda Casari Open Source Programs Office, Google, Katie McLaughlin Open Source Programs Office, Google, Milo Trujillo University of Vermont, Laurent Hébert-Dufresne University of Vermont, James P. Bagrow University of Vermont
Pre-print Media Attached
17:19
4m
Talk
On Improving Deep Learning Trace Analysis with System Call Arguments
Technical Papers
Quentin Fournier Polytechnique Montréal, Daniel Aloise Polytechnique Montréal, Seyed Vahid Azhari Ciena, François Tetreault Ciena
Pre-print
17:23
27m
Live Q&A
Discussions and Q&A
Technical Papers

Wed 19 May

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

02:00 - 02:50
02:01
4m
Talk
Practitioners' Perceptions of the Goals and Visual Explanations of Defect Prediction Models
Technical Papers
Jirayus Jiarpakdee Monash University, Australia, Chakkrit Tantithamthavorn Monash University, John Grundy Monash University
Pre-print
02:05
3m
Talk
On the Effectiveness of Deep Vulnerability Detectors to Simple Stupid Bug Detection
Mining Challenge
Jiayi Hua Beijing University of Posts and Telecommunications, Haoyu Wang Beijing University of Posts and Telecommunications
Pre-print
02:08
4m
Talk
An Empirical Study of OSS-Fuzz Bugs
Technical Papers
Zhen Yu Ding Motional, Claire Le Goues Carnegie Mellon University
Pre-print
02:12
3m
Talk
Denchmark: A Bug Benchmark of Deep Learning-related Software
Data Showcase
Misoo Kim Sungkyunkwan University, Youngkyoung Kim Sungkyunkwan University, Eunseok Lee Sungkyunkwan University
02:15
4m
Talk
JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction
Technical Papers
Chanathip Pornprasit Monash University, Chakkrit Tantithamthavorn Monash University
Pre-print
02:19
31m
Live Q&A
Discussions and Q&A
Technical Papers

02:00 - 02:50
NLPRegistered Reports / Technical Papers at MSR Room 2
Chair(s): Chunyang Chen Monash University
02:01
4m
Talk
Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions
Technical Papers
SOFONIAS YITAGESU Tianjin University, Xiaowang Zhang Tianjin University, Zhiyong Feng Tianjin University, Li Xiaohong TianJin University, Zhenchang Xing Australian National University
Pre-print
02:05
4m
Talk
Attention-based model for predicting question relatedness on Stack Overflow
Technical Papers
Jiayan Pei South China University of Technology, Yimin Wu South China University of Technology, Research Institute of SCUT in Yangjiang, Zishan Qin South China University of Technology, Yao Cong South China University of Technology, Jingtao Guan Research Institute of SCUT in Yangjiang
Pre-print
02:09
4m
Talk
Characterising the Knowledge about Primitive Variables in Java Code Comments
Technical Papers
Mahfouth Alghamdi The University of Adelaide, Shinpei Hayashi Tokyo Institute of Technology, Takashi Kobayashi Tokyo Institute of Technology, Christoph Treude University of Adelaide
Pre-print
02:13
4m
Talk
Googling for Software Development: What Developers Search For and What They Find
Technical Papers
Pre-print
02:17
3m
Talk
Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews
Registered Reports
Mohammad Abdul Hadi University of British Columbia, Fatemeh Hendijani Fard University of British Columbia
Pre-print
02:20
3m
Talk
Cross-status Communication and Project Outcomes in OSS Development–A Language Style Matching Perspective
Registered Reports
Yisi Han Nanjing University, Zhendong Wang University of California, Irvine, Yang Feng State Key Laboratory for Novel Software Technology, Nanjing University, Zhihong Zhao Nanjing Tech Unniversity, Yi Wang Beijing University of Posts and Telecommunications
Pre-print
02:23
27m
Live Q&A
Discussions and Q&A
Technical Papers

03:10 - 04:00
03:10
50m
Tutorial
Elasticsearch Full-Text Search Internals
Tutorials
10:00 - 10:50
DatasetsData Showcase / Technical Papers at MSR Room 1
Chair(s): Sridhar Chimalakonda Indian Institute of Technology Tirupati
10:01
3m
Talk
AndroidCompass: A Dataset of Android Compatibility Checks in Code Repositories
Data Showcase
Sebastian Nielebock Otto-von-Guericke University Magdeburg, Germany, Paul Blockhaus Otto-von-Guericke-University Magdeburg, Germany, Jacob Krüger Otto von Guericke University Magdeburg, Frank Ortmeier Otto-von-Guericke-University Magdeburg, Faculty of Computer Science, Chair of Software Engineering
Pre-print Media Attached
10:04
3m
Talk
GE526: A Dataset of Open Source Game Engines
Data Showcase
Dheeraj Vagavolu Indian Institute of Technology Tirupati, Vartika Agrahari Indian Institute of Technology Tirupati, Sridhar Chimalakonda Indian Institute of Technology Tirupati, Akhila Sri Manasa Venigalla IIT Tirupati, India
10:07
3m
Talk
Andromeda: A Dataset of Ansible Galaxy Roles and Their Evolution
Data Showcase
Ruben Opdebeeck Vrije Universiteit Brussel, Ahmed Zerouali Vrije Universiteit Brussel, Coen De Roover Vrije Universiteit Brussel
10:10
3m
Talk
The Wonderless Dataset for Serverless Computing
Data Showcase
Nafise Eskandani TU Darmstadt, Guido Salvaneschi University of St. Gallen
Pre-print
10:13
3m
Talk
DUETS: A Dataset of Reproducible Pairs of Java Library-Clients
Data Showcase
Thomas Durieux KTH Royal Institute of Technology, Sweden, César Soto-Valero KTH Royal Institute of Technology, Benoit Baudry KTH Royal Institute of Technology
Pre-print
10:16
3m
Talk
EQBENCH: A Dataset of Equivalent and Non-equivalent Program Pairs
Data Showcase
Sahar Badihi University of British Columbia, Canada, Yi Li Nanyang Technological University, Singapore, Julia Rubin University of British Columbia, Canada
10:19
31m
Live Q&A
Discussions and Q&A
Technical Papers

10:00 - 10:50
Dependencies and OSSTechnical Papers / Registered Reports at MSR Room 2
Chair(s): Luca Pascarella Delft University of Technology
10:01
3m
Talk
Identifying Critical Projects via PageRank and Truck Factor
Technical Papers
Rolf-Helge Pfeiffer IT University of Copenhagen
Pre-print
10:04
4m
Talk
Revisiting Dockerfiles in Open Source Software Over Time
Technical Papers
Kalvin Eng University of Alberta, Abram Hindle University of Alberta
Pre-print
10:08
3m
Talk
Does the First-Response Matter for Future Contributions? A Study of First Contributions
Registered Reports
Noppadol Assavakamhaenghan Nara Institute of Science and Technology, Supatsara Wattanakriengkrai Nara Institute of Science and Technology, Naomichi Shimada Nara Institute of Science and Technology, Raula Gaikovina Kula NAIST, Takashi Ishio Nara Institute of Science and Technology, Kenichi Matsumoto Nara Institute of Science and Technology
Pre-print
10:11
4m
Talk
Data Balancing Improves Self-Admitted Technical Debt Detection
Technical Papers
Murali Sridharan University of Oulu, Leevi Rantala University of Oulu, Maëlick Claes University of Oulu, Mika Mäntylä University of Oulu
Pre-print
10:15
35m
Live Q&A
Discussions and Q&A
Technical Papers

17:00 - 17:50
Energy, logging, and APIsTechnical Papers at MSR Room 1
Chair(s): Akond Rahman Tennessee Tech University
17:01
3m
Talk
S3M: Siamese Stack (Trace) Similarity Measure
Technical Papers
Aleksandr Khvorov JetBrains, ITMO University, Roman Vasiliev JetBrains, George Chernishev Saint-Petersburg State University, Irving Muller Rodrigues Polytechnique Montreal, Montreal, Canada, Dmitrij Koznov Saint-Petersburg State University, Nikita Povarov JetBrains
Pre-print
17:04
4m
Talk
Mining the ROS ecosystem for Green Architectural Tactics in Robotics and an Empirical Evaluation
Technical Papers
Ivano Malavolta Vrije Universiteit Amsterdam, Katerina Chinnappan Vrije Universiteit Amsterdam, Stan Swanborn Vrije Universiteit Amsterdam, The Netherlands, Grace Lewis Carnegie Mellon Software Engineering Institute, Patricia Lago Vrije Universiteit Amsterdam
Pre-print Media Attached
17:08
4m
Talk
Mining Energy-Related Practices in Robotics Software
Technical Papers
Michel Albonico UTFPR, Ivano Malavolta Vrije Universiteit Amsterdam, Gustavo Pinto Federal University of Pará, Emitzá Guzmán Vrije Universiteit Amsterdam, Katerina Chinnappan Vrije Universiteit Amsterdam, Patricia Lago Vrije Universiteit Amsterdam
Pre-print Media Attached
17:12
3m
Talk
Mining API Interactions to Analyze Software Revisions for the Evolution of Energy Consumption
Technical Papers
Andreas Schuler University of Applied Sciences Upper Austria, Gabriele Anderst-Kotsis Johannes Kepler University, Linz, Austria
Pre-print
17:15
4m
Talk
Can I Solve it? Identifying the APIs required to complete OSS tasks
Technical Papers
Fabio Marcos De Abreu Santos Northern Arizona University, USA, Igor Scaliante Wiese Federal University of Technology – Paraná - UTFPR, Bianca Trinkenreich Northern of Arizona Univeristy, Igor Steinmacher Federal University of Technology - Paraná / Northern Arizona University, Anita Sarma Oregon State University, Marco Gerosa Northern Arizona University, USA
Pre-print
17:19
31m
Live Q&A
Discussions and Q&A
Technical Papers

17:00 - 17:50
Change Management and AnalysisTechnical Papers / Registered Reports at MSR Room 2
Chair(s): Sarah Nadi University of Alberta
17:01
4m
Talk
Studying the Change Histories of Stack Overflow and GitHub Snippets
Technical Papers
Saraj Singh Manes Carleton University, Olga Baysal Carleton University
Pre-print
17:05
4m
Talk
Learning Off-By-One Mistakes: An Empirical Study
Technical Papers
Hendrig Sellik Delft University of Technology, Onno van Paridon Adyen N.V., Georgios Gousios Facebook & Delft University of Technology, Maurício Aniche Delft University of Technology
Pre-print
17:09
4m
Talk
Predicting Design Impactful Changes in Modern Code Review: A Large-Scale Empirical Study
Technical Papers
Anderson Uchôa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Caio Barbosa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Daniel Coutinho Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Willian Oizumi Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Wesley Assunção Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Silvia Regina Vergilio Federal University of Paraná, Juliana Alves Pereira PUC-Rio, Anderson Oliveira PUC-Rio, Alessandro Garcia PUC-Rio
Pre-print
17:13
4m
Talk
Rollback Edit Inconsistencies in Developer Forum
Technical Papers
Saikat Mondal University of Saskatchewan, Gias Uddin University of Calgary, Canada, Chanchal K. Roy University of Saskatchewan
Pre-print
17:17
3m
Talk
Assessing the Exposure of Software Changes: The DiPiDi Approach
Registered Reports
Mehran Meidani University of Waterloo, Maxime Lamothe University of Waterloo, Shane McIntosh
Pre-print
17:20
4m
Talk
On the Use of Dependabot Security Pull Requests
Technical Papers
Mahmoud Alfadel Concordia Univerisity, Diego Costa Concordia University, Canada, Emad Shihab Concordia University, Mouafak Mkhallalati Concordia University
Pre-print
17:24
26m
Live Q&A
Discussions and Q&A
Technical Papers

Call for Mining Challenge Papers

This year, the mining challenge is about ManySStuBs4J, a dataset of fixes to Java simple bugs. The dataset focuses on “SStuBs“, i.e., simple stupid bugs. SStuBs are bugs that appear on a single statement and the corresponding fix is within that statement.

The dataset was collected to facilitate the study of such bugs towards addressing empirical questions about these bugs and related program repair techniques. The included fixes are classified — where possible — into one of 16 syntactic templates, such as accidentally swapped method arguments, incorrect operator usage, or wrong variable usage. For each bug in the challenge dataset, we include the provenance of the bug (GitHub project, commit SHA), the diff between the buggy and fixed version of the files, and an annotation of which (if any) of the 16 SStuBs patterns it matches.

In this challenge, participants can use two variants of the dataset. A small version of the dataset that contains 25,539 SStuBs changes mined from 100 Java projects in GitHub that use Maven. These projects can be built and tested (if they contain tests) in an automated fashion. The large version of the data set contains 153,652 SStuBs mined from 1,000 popular open-source Java projects in GitHub, but not all of these projects use Maven, so it may not be feasible to build and test them.

The challenge is open-ended: participants can choose the research questions that they find most interesting. Our suggestions include:

  • Bug detection: What methods are most effective for locating SStuBs?
  • Program repair: What methods are most effective for proposing repairs to SStuBs? This could be a separate step or combined.
  • Why SStubS occur: What context do SStuBs appear in? What are common root causes? Are there characteristics of the software project, the development team, or the individual source file that make SStuBs more likely to appear?
  • What encourages fixing SStuBs: What factors characterize SStuBs that are more quickly found and fixed?
  • Testing: How is testing related to SStuBs? Do projects with more or better unit tests have fewer or easier-to-fix SStuBs?

These are just some of the questions that could be answered using the ManySStuBs4J dataset. Participants may combine the SStuBs data with other code or metadata: for example, data about project popularity or contributor experience. We will not provide such data, but participants are encouraged to “bring their own data” (BYOD) by joining SStuBs data with data from other public, readily available, sources such as GHTorrent or GitHub. We ask the participants to carefully consider any ethical implications that stem from using other sources of data, such as the use of personally identifiable information.

How to Participate in the Challenge

First, familiarize yourself with the ManySStuBs4J dataset:

  • Read the MSR 2020 paper about ManySStuBs4J.
  • Study the download page of ManySStuBs4J, which includes the most recent version and links to download the dataset as well as the documentation page.
  • Create a new issue here in case you have problems with the dataset or want to suggest ideas for improvements.

Finally, use the dataset to answer your research questions, report your findings in a four-page challenge paper (see information below), submit your abstract before January 19, 2021, and your final paper before January 26, 2021. If your paper is accepted, present your results at MSR 2021 in Madrid, Spain!

Join us on Slack for informal discussions among participants at http://msr2021challenge.slack.com/

Submission

A challenge paper should describe the results of your work by providing an introduction to the problem you address and why it is worth studying, the version of the dataset you used, the approach and tools you used, your results and their implications, and conclusions. Make sure your report highlights the contributions and the importance of your work. See also our open science policy regarding the publication of software and additional data you used for the challenge.

Challenge papers must not exceed 4 pages plus 1 additional page only with references and must conform to the MSR 2021 format and submission guidelines. Each submission will be reviewed by at least three members of the program committee. Submissions should follow the IEEE Conference Proceedings Formatting Guidelines, with title in 24pt font and full text in 10pt type. LaTEX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option.

IMPORTANT: The mining challenge track of MSR 2021 follows the double-blind submission model. Submissions should not reveal the identity of the authors in any way. This means that authors should:

  • leave out author names and affiliations from the body and metadata of the submitted pdf
  • ensure that any citations to related work by themselves are written in the third person, for example “the prior work of XYZ” as opposed to “our prior work [2]”
  • not refer to their personal, lab or university website; similarly, care should be taken with personal accounts on GitHub, BitBucket, Google Drive, etc.
  • not upload unblinded versions of their paper on archival websites during bidding/reviewing, however uploading unblinded versions prior to submission is allowed and sometimes unavoidable (e.g., thesis)

Authors having further questions on double blind reviewing are encouraged to contact the Mining Challenge Chairs via email.

Papers must be submitted electronically through HotCRP, should not have been published elsewhere, and should not be under review or submitted for review elsewhere for the duration of consideration. ACM plagiarism policy and procedures shall be followed for cases of double submission. The submission must also comply with the IEEE Policy on Authorship.

Upon notification of acceptance, all authors of accepted papers will be asked to complete a copyright form and will receive further instructions for preparing their camera ready versions. At least one author of each accepted paper is expected to register and present the results at MSR 2021. All accepted contributions will be published in the electronic conference proceedings.

This year’s mining challenge can be cited as:

title={MSR Mining Challenge: The Life of Simple, Stupid Bugs (SStubS)},
author={Karampatsis, Rafael-Michael and Allamanis, Miltiadis and Sutton, Charles},
year={2021},
booktitle={Proceedings of the International Conference on Mining Software Repositories (MSR 2021)},
}

The dataset itself can be cited as:

@inproceedings{sstubs,
title={How Often Do Single-Statement Bugs Occur? The ManySStuBs4J Dataset},
author={Karampatsis, Rafael-Michael and Sutton, Charles},
year={2020},
booktitle={Proceedings of the International Conference on Mining Software Repositories (MSR 2020)},
preprint={https://arxiv.org/abs/1905.13334}
}

Open Science Policy

Openness in science is key to fostering progress via transparency, reproducibility and replicability. Our steering principle is that all research output should be accessible to the public and that empirical studies should be reproducible. In particular, we actively support the adoption of open data and open source principles. To increase reproducibility and replicability, we encourage all contributing authors to disclose:

  • the source code of the software they used to retrieve and analyze the data
  • the (anonymized and curated) empirical data they retrieved in addition to the SOTorrent dataset
  • a document with instructions for other researchers describing how to reproduce or replicate the results

Already upon submission, authors can privately share their anonymized data and software on archives such as Zenodo or Figshare (tutorial available here). Zenodo accepts up to 50GB per dataset (more upon request). There is no need to use Dropbox or Google Drive. After acceptance, data and software should be made public so that they receive a DOI and become citable. Zenodo and Figshare accounts can easily be linked with GitHub repositories to automatically archive software releases. In the unlikely case that authors need to upload terabytes of data, Archive.org may be used.

We recognise that anonymising artifacts such as source code is more difficult than preserving anonymity in a paper. We ask authors to take a best effort approach to not reveal their identities. We will also ask reviewers to avoid trying to identify authors by looking at commit histories and other such information that is not easily anonymised. Authors wanting to share GitHub repositories may want to look into using https://anonymous.4open.science/ which is an open source tool that helps you to quickly double-blind your repository.

We encourage authors to self-archive pre- and postprints of their papers in open, preserved repositories such as arXiv.org. This is legal and allowed by all major publishers including ACM and IEEE and it lets anybody in the world reach your paper. Note that you are usually not allowed to self-archive the PDF of the published article (that is, the publisher proof or the Digital Library version).

Please note that the success of the open science initiative depends on the willingness (and possibilities) of authors to disclose their data and that all submissions will undergo the same review process independent of whether or not they disclose their analysis code or data. We encourage authors who cannot disclose industrial or otherwise non-public data, for instance due to non-disclosure agreements, to provide an explicit (short) statement in the paper.

Best Mining Challenge Paper Award

As mentioned above, all submissions will undergo the same review process independent of whether or not they disclose their analysis code or data. However, only accepted papers for which code and data are available on preserved archives, as described in the open science policy, will be considered by the program committee for the best mining challenge paper award.

Best Student Presentation Award

Like in the previous years, there will be a public voting during the conference to select the best mining challenge presentation. This award often goes to authors of compelling work who present an engaging story to the audience. Only students can compete for this award.

One of the secret ingredients behind the success of the International Conference on Mining Software Repositories (MSR) is its annual Mining Challenge, in which MSR participants can showcase their techniques, tools and creativity on a common data set. In true MSR fashion, this data set is a “real” data set contributed by researchers in the community, solicited through an open call. There are many benefits of sharing a data set for the MSR Mining Challenge. The selected challenge proposal explaining the data set will appear in the MSR 2021 proceedings, and the challenge papers using the data set will be required to cite the challenge proposal or an existing paper of the researchers about the selected data set. Furthermore, the authors of the data set will become the official 2021 Mining Challenge Chairs, responsible for the reviewing process (e.g., composing a Challenge PC, managing the submissions and review assignments, etc.). Finally, it is not uncommon for challenge data sets to feature in MSR and other publications well after the conference is finished! If you would like to compete for a chance to have your data set featured in the 2021 MSR Mining Challenge and all the benefits that come with it, please submit a 1-page proposal with up to 3 pages of appendix at https://msr2021.hotcrp.com/, containing the following information:

  1. Title of data set.
  2. What does your data set contain?
  3. How large is it?
  4. How accessible is it and how can the data be obtained?
  5. How representative is it?
  6. Does it require specialized tools to mine it?
  7. What would challenge participants need to work with the data set?
  8. What kind of questions do you expect challenge participants to answer?
  9. A link to a small sample of the data (e.g., via dropbox, github, etc.).

The above conform to the IEEE formatting instructions IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options). For more information see here: https://www.ieee.org/conferences/publishing/templates.html Once the winning proposal will be selected, its authors will become the MSR 2021 Challenge Chairs and will be responsible for choosing the MSR 2021 Mining Challenge program committee. The major deadline for this is the 15th of September 2020, at which time the Challenge CFP along with the PC will be announced, and the full challenge data set will be publicly released. By making the challenge data set available by early fall, we hope that many student teams will be able to use the challenge data set for their graduate class projects.

Timeline:

  • Deadline for proposals: August 14th, 2020
  • Proposal accepted and all submitters notified: August 21st, 2020
  • Challenge CFP: September 16th, 2020
  • Challenge PC formed: September 16th, 2020
  • Challenge data made available: September 14th, 2020
  • Challenge papers deadline: Feb 19th, 2021 (tentative)