Mon 15 AprDisplayed time zone: Lisbon change
09:00 - 10:30 | Day 1: OpeningTechnical Papers / MSR Awards / Social Events / Tutorials / Data and Tool Showcase Track / Mining Challenge / Registered Reports / Industry Track / MIP Award / Vision and Reflection / Keynotes at Grande Auditório Chair(s): Diomidis Spinellis Athens University of Economics and Business & Delft University of Technology | ||
09:00 30mDay opening | Opening Session & Award Announcements MSR Awards | ||
09:30 30mAwards | MSR 2024 Foundational Contribution Award talk MSR Awards Margaret-Anne Storey University of Victoria | ||
10:00 30mTalk | Most Influential Paper Award talk MIP Award Eirini Kalliamvakou GitHub | ||
10:30 - 11:00 | Coffee for MSR newcomersSocial Events at Open Space (reserved area) Chair(s): Federica Sarro University College London, Alexander Serebrenik Eindhoven University of Technology | ||
10:30 30mCoffee break | Coffee for MSR newcomers Social Events | ||
11:00 - 12:30 | Ecosystems, Reuse and APIs & TutorialsData and Tool Showcase Track / Technical Papers / Tutorials at Almada Negreiros Chair(s): Mahmoud Alfadel University of Waterloo, Ayushi Rastogi University of Groningen, The Netherlands | ||
11:00 12mTalk | Thirty-Three Years of Mathematicians and Software Engineers: A Case Study of Domain Expertise and Participation in Proof Assistant Ecosystems Technical Papers Gwenyth Lincroft Northeastern University, Minsung Cho Northeastern University, Mahsa Bazzaz Northeastern University, Katherine Hough Northeastern University, Jonathan Bell Northeastern University Pre-print Media Attached | ||
11:12 12mTalk | Boosting API Misuse Detection via Integrating API Constraints from Multiple Sources Technical Papers Can Li Nanjing University of Aeronautics and Astronautics, Jingxuan Zhang Nanjing University of Aeronautics and Astronautics, Yixuan Tang Nanjing University of Aeronautics and Astronautics, Zhuhang Li Nanjing University of Aeronautics and Astronautics, Tianyue Sun Nanjing University of Aeronautics and Astronautics | ||
11:24 6mTalk | Availability and Usage of Platform-Specific APIs: A First Empirical Study Technical Papers Pre-print Media Attached File Attached | ||
11:30 4mTalk | AndroLibZoo: A Reliable Dataset of Libraries Based on Software Dependency Analysis Data and Tool Showcase Track Jordan Samhi CISPA Helmholtz Center for Information Security, Tegawendé F. Bissyandé University of Luxembourg, Jacques Klein University of Luxembourg | ||
11:34 4mTalk | Goblin: A Framework for Enriching and Querying the Maven Central Dependency Graph Data and Tool Showcase Track Damien Jaime Sorbonne Université - Lip6 - SAP, Joyce El Haddad Paris Dauphine-PSL Université, CNRS, LAMSADE, Pascal Poizat Université Paris Nanterre & LIP6 Pre-print File Attached | ||
11:38 4mTalk | Dataset: Copy-based Reuse in Open Source Software Data and Tool Showcase Track Mahmoud Jahanshahi Research Assistant, University of Tennessee Knoxville, Audris Mockus The University of Tennessee & Vilnius University Pre-print | ||
11:45 45mTalk | Mining Our Way Back to Incremental Builds for DevOps Pipelines Tutorials Shane McIntosh University of Waterloo Pre-print | ||
11:00 - 12:30 | Defects, Bugs and IssuesTechnical Papers / MSR Awards / Social Events / Tutorials / Data and Tool Showcase Track / Mining Challenge / Registered Reports / Industry Track / MIP Award / Vision and Reflection / Keynotes at Grande Auditório Chair(s): Wesley Assunção North Carolina State University | ||
11:00 12mTalk | Enhancing Performance Bug Prediction Using Performance Code Metrics Technical Papers Guoliang Zhao Computer Science of Queen's University, Stefanos Georgio , Safwat Hassan University of Toronto, Canada, Ying Zou Queen's University, Kingston, Ontario, Derek Truong IBM Canada, Toby Corbin IBM UK | ||
11:12 12mTalk | CrashJS: A NodeJS Benchmark for Automated Crash Reproduction Technical Papers Philip Oliver Victoria University of Wellington, Jens Dietrich Victoria University of Wellington, Craig Anslow Victoria University of Wellington, Michael Homer Victoria University of Wellington | ||
11:24 12mTalk | An Empirical Study on Just-in-time Conformal Defect Prediction Technical Papers Xhulja Shahini paluno - University of Duisburg-Essen, Andreas Metzger University of Duisburg-Essen, Klaus Pohl | ||
11:36 12mTalk | Fine-Grained Just-In-Time Defect Prediction at the Block Level in Infrastructure-as-Code (IaC) Technical Papers Mahi Begoug , Moataz Chouchen ETS, Ali Ouni ETS Montreal, University of Quebec, Eman Abdullah AlOmar Stevens Institute of Technology, Mohamed Wiem Mkaouer University of Michigan - Flint | ||
11:48 4mTalk | TrickyBugs: A Dataset of Corner-case Bugs in Plausible Programs Data and Tool Showcase Track Kaibo Liu Peking University, Yudong Han Peking University, Yiyang Liu Peking University, Zhenpeng Chen Nanyang Technological University, Jie M. Zhang King's College London, Federica Sarro University College London, Gang Huang Peking University, Yun Ma Peking University | ||
11:52 4mTalk | GitBugs-Java: A Reproducible Java Benchmark of Recent Bugs Data and Tool Showcase Track André Silva KTH Royal Institute of Technology, Nuno Saavedra INESC-ID and IST, University of Lisbon, Martin Monperrus KTH Royal Institute of Technology | ||
11:56 4mTalk | A Dataset of Partial Program Fixes Data and Tool Showcase Track Dirk Beyer LMU Munich, Lars Grunske Humboldt-Universität zu Berlin, Matthias Kettl LMU Munich, Marian Lingsch-Rosenfeld LMU Munich, Moeketsi Raselimo Humboldt-Universität zu Berlin | ||
12:00 4mTalk | BugsPHP: A dataset for Automated Program Repair in PHP Data and Tool Showcase Track K.D. Pramod University of Moratuwa, Sri Lanka, W.T.N. De Silva University of Moratuwa, Sri Lanka, W.U.K. Thabrew University of Moratuwa, Sri Lanka, Ridwan Salihin Shariffdeen National University of Singapore, Sandareka Wickramanayake University of Moratuwa, Sri Lanka Pre-print | ||
12:04 4mTalk | AW4C: A Commit-Aware C Dataset for Actionable Warning Identification Data and Tool Showcase Track Zhipeng Liu , Meng Yan Chongqing University, Zhipeng Gao Shanghai Institute for Advanced Study - Zhejiang University, Dong Li , Xiaohong Zhang Chongqing University, Dan Yang Chongqing University | ||
12:08 5mTalk | Predicting the Impact of Crashes Across Release Channels Industry Track | ||
12:13 5mTalk | Zero Shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis Industry Track | ||
14:00 - 15:30 | Mining ChallengeMining Challenge at Almada Negreiros Chair(s): Preetha Chatterjee Drexel University, USA, Fabio Palomba University of Salerno | ||
14:00 5mTalk | ChatGPT Chats Decoded: Uncovering Prompt Patterns for Superior Solutions in Software Development Lifecycle Mining Challenge Liangxuan Wu Huazhong University of Science and Technology, Yanjie Zhao Huazhong University of Science and Technology, Xinyi Hou Huazhong University of Science and Technology, Tianming Liu Monash Univerisity, Haoyu Wang Huazhong University of Science and Technology | ||
14:05 5mTalk | Write me this Code: An Analysis of ChatGPT Quality for Producing Source Code Mining Challenge Konstantinos Moratis Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Themistoklis Diamantopoulos Electrical and Computer Engineering Dept, Aristotle University of Thessaloniki, Dimitrios-Nikitas Nastos Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Andreas Symeonidis Aristotle University of Thessaloniki Pre-print | ||
14:10 5mTalk | Quality Assessment of ChatGPT Generated Code and their Use by Developers Mining Challenge Mohammed Latif Siddiq University of Notre Dame, Lindsay Roney University of Notre Dame, Jiahao Zhang , Joanna C. S. Santos University of Notre Dame Pre-print Media Attached File Attached | ||
14:15 5mTalk | Analyzing Developer Use of ChatGPT Generated Code in Open Source GitHub Projects Mining Challenge Balreet Grewal University of Alberta, Wentao Lu University of Alberta, Sarah Nadi New York University Abu Dhabi, University of Alberta, Cor-Paul Bezemer University of Alberta Pre-print | ||
14:20 5mTalk | How I Learned to Stop Worrying and Love ChatGPT Mining Challenge Piotr Przymus Nicolaus Copernicus University in Toruń, Poland, Mikołaj Fejzer Nicolaus Copernicus University in Toruń, Jakub Narębski Nicolaus Copernicus University in Toruń, Krzysztof Stencel University of Warsaw Pre-print | ||
14:25 5mTalk | Can ChatGPT Support Developers? An Empirical Evaluation of Large Language Models for Code Generation. Mining Challenge Kailun Jin York University, Chung-Yu Wang York University, Hung Viet Pham York University, Hadi Hemmati York University Pre-print | ||
14:30 5mTalk | The role of library versions in Developer-ChatGPT conversations Mining Challenge Pre-print | ||
14:35 5mTalk | AI Writes, We Analyze: The ChatGPT Python Code Saga Mining Challenge Md Fazle Rabbi Idaho State University, Arifa Islam Champa Idaho State University, Minhaz F. Zibran Idaho State University, Md Rakibul Islam Lamar University DOI Pre-print | ||
14:40 5mTalk | ChatGPT in Action: Analyzing Its Use in Software Development Mining Challenge Arifa Islam Champa Idaho State University, Md Fazle Rabbi Idaho State University, Costain Nachuma Idaho State University, Minhaz F. Zibran Idaho State University DOI Pre-print | ||
14:45 5mTalk | Chatting with AI: Deciphering Developer Conversations with ChatGPT Mining Challenge Suad Mohamed Belmont University, Abdullah Parvin Belmont University, Esteban Parra Belmont University | ||
14:50 5mTalk | Does Generative AI Generate Smells Related to Container Orchestration?: An Exploratory Study with Kubernetes Manifests Mining Challenge Yue Zhang Auburn University, Rachel Meredith Auburn University, Wilson Reaves Auburn University, Julia Coriolano Federal University of Pernambuco, Muhammad Ali Babar School of Computer Science, The University of Adelaide, Akond Rahman Auburn University Pre-print | ||
14:55 5mTalk | On the Taxonomy of Developers' Discussion Topics with ChatGPT Mining Challenge | ||
15:00 5mTalk | How to refactor this code? An exploratory study on developer-ChatGPT refactoring conversations Mining Challenge Eman Abdullah AlOmar Stevens Institute of Technology, AnushKrishna Venkatakrishnan Rochester Institute of Technology, USA, Mohamed Wiem Mkaouer University of Michigan - Flint, Christian Newman , Ali Ouni ETS Montreal, University of Quebec | ||
15:05 5mTalk | Analyzing Developer-ChatGPT Conversations for Software Refactoring: An Exploratory Study Mining Challenge Omkar Sandip Chavan Rochester Institute of Technology, Divya Dilip Hinge Rochester Institute of Technology, Soham Sanjay Deo Rochester Institute of Technology, Yaxuan (Olivia) Wang Rochester Institute of Technology, Mohamed Wiem Mkaouer University of Michigan - Flint | ||
15:10 5mTalk | How Do Software Developers Use ChatGPT? An Exploratory Study on GitHub Pull Requests Mining Challenge Moataz Chouchen ETS, Narjes Bessghaier ETS Montreal, University of Quebec, Mahi Begoug , Ali Ouni ETS Montreal, University of Quebec, Eman Abdullah AlOmar Stevens Institute of Technology, Mohamed Wiem Mkaouer University of Michigan - Flint | ||
15:15 5mTalk | Investigating the Utility of ChatGPT in the Issue Tracking System: An Exploratory Study Mining Challenge Joy Krishan Das University of Saskatchewan, Saikat Mondal University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Canada Pre-print | ||
15:20 5mTalk | Enhancing User Interaction in ChatGPT: Characterizing and Consolidating Multiple Prompts for Issue Resolution Mining Challenge Saikat Mondal University of Saskatchewan, Suborno Deb Bappon Department of Computer Science, University of Saskatchewan, Canada, Chanchal K. Roy University of Saskatchewan, Canada Pre-print | ||
14:00 - 15:30 | Software QualityTechnical Papers / Registered Reports / Data and Tool Showcase Track at Grande Auditório Chair(s): Gopi Krishnan Rajbahadur Centre for Software Excellence, Huawei, Canada | ||
14:00 12mTalk | Not all Dockerfile Smells are the Same: An Empirical Evaluation of Hadolint Writing Practices by Experts Technical Papers Giovanni Rosa University of Molise, Simone Scalabrino University of Molise, Gregorio Robles Universidad Rey Juan Carlos, Rocco Oliveto University of Molise | ||
14:12 12mTalk | Supporting High-Level to Low-Level Requirements Coverage Reviewing with Large Language Models Technical Papers Anamaria-Roberta Hartl Johannes Kepler University Linz, Christoph Mayr-Dorn JOHANNES KEPLER UNIVERSITY LINZ, Atif Mashkoor Johannes Kepler University Linz, Alexander Egyed Johannes Kepler University Linz DOI Authorizer link Pre-print | ||
14:24 12mTalk | On the Executability of R Markdown Files Technical Papers Md Anaytul Islam Lakehead University, Muhammad Asaduzzman University of Windsor, Shaowei Wang Department of Computer Science, University of Manitoba, Canada | ||
14:36 12mTalk | APIstic: A Large Collection of OpenAPI Metrics Technical Papers souhaila serbout Software Institute @ USI, Cesare Pautasso Software Institute, Faculty of Informatics, USI Lugano | ||
14:48 6mTalk | Improving Automated Code Reviews: Learning From Experience Technical Papers Hong Yi Lin The University of Melbourne, Patanamon Thongtanunam University of Melbourne, Christoph Treude Singapore Management University, Wachiraphan (Ping) Charoenwet The University of Melbourne | ||
14:55 4mTalk | Multi-faceted Code Smell Detection at Scale using DesigniteJava 2.0 Data and Tool Showcase Track Tushar Sharma Dalhousie University Pre-print | ||
14:59 4mTalk | SATDAUG - A Balanced and Augmented Dataset for Detecting Self-Admitted Technical Debt Data and Tool Showcase Track Edi Sutoyo Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Andrea Capiluppi University of Groningen | ||
15:03 4mTalk | Curated Email-Based Code Reviews Datasets Data and Tool Showcase Track Mingzhao Liang The University of Melbourne, Wachiraphan (Ping) Charoenwet The University of Melbourne, Patanamon Thongtanunam University of Melbourne | ||
15:07 4mTalk | TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution Data and Tool Showcase Track Andre Hora UFMG Pre-print Media Attached | ||
15:11 4mTalk | Greenlight: Highlighting TensorFlow APIs Energy Footprint Data and Tool Showcase Track Saurabhsingh Rajput Dalhousie University, Maria Kechagia University College London, Federica Sarro University College London, Tushar Sharma Dalhousie University Pre-print | ||
15:15 5mTalk | When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems Registered Reports Gilberto Recupito University of Salerno, Giammaria Giordano University of Salerno, Filomena Ferrucci University of Salerno, Dario Di Nucci University of Salerno, Fabio Palomba University of Salerno | ||
15:20 5mTalk | Comparison of Static Analysis Architecture Recovery Tools for Microservice Applications Registered Reports Simon Schneider Hamburg University of Technology, Alexander Bakhtin University of Oulu, Xiaozhou Li University of Oulu, Jacopo Soldani University of Pisa, Italy, Antonio Brogi Università di Pisa, Tomas Cerny University of Arizona, Riccardo Scandariato Hamburg University of Technology, Davide Taibi University of Oulu and Tampere University | ||
16:00 - 17:30 | Mobile AppsData and Tool Showcase Track / Technical Papers at Almada Negreiros Chair(s): Dario Di Nucci University of Salerno | ||
16:00 12mTalk | Automating GUI-based Test Oracles for Mobile Apps Technical Papers Kesina Baral CQSE America, Jack Johnson , Junayed Mahmud George Mason University, Sabiha Salma George Mason University, Mattia Fazzini University of Minnesota, Julia Rubin University of British Columbia, Jeff Offutt George Mason University, Kevin Moran University of Central Florida | ||
16:12 12mTalk | Global Prosperity or Local Monopoly? Understanding the Geography of App Popularity Technical Papers Liu Wang Beijing University of Posts and Telecommunications, Conghui Zheng Beijing University of Posts and Telecommunications, Haoyu Wang Huazhong University of Science and Technology, Xiapu Luo The Hong Kong Polytechnic University, Gareth Tyson Queen Mary University of London, Yi Wang , Shangguang Wang Beijing University of Posts and Telecommunications | ||
16:24 12mTalk | GuiEvo: Automated Evolution of Mobile App UIs Technical Papers Sabiha Salma George Mason University, S M Hasan Mansur George Mason University, Yule Zhang George Mason University, Kevin Moran University of Central Florida | ||
16:36 12mTalk | Comparing Apples to Androids: Discovery, Retrieval, and Matching of iOS and Android Apps for Cross-Platform Analyses Technical Papers Magdalena Steinböck TU Wien, Jakob Bleier TU Wien, Mikka Rainer CISPA Helmholtz Center for Information Security, Tobias Urban Institute for Internet Security & secunet Security Networks AG, Christine Utz CISPA Helmholtz Center for Information Security, Martina Lindorfer TU Wien | ||
16:48 12mTalk | Keep Me Updated: An Empirical Study on Embedded Javascript Engines in Android Apps Technical Papers Elliott Wen The University of Auckland, Jiaxiang Liu The Hong Kong Polytechnic University, Xiapu Luo The Hong Kong Polytechnic University, Giovanni Russello University of Auckland, Jens Dietrich Victoria University of Wellington | ||
17:00 12mTalk | Large Language Model vs. Stack Overflow in Addressing Android Permission Related Challenges Technical Papers Sahrima Jannat Oishwee University of Saskatchewan, Natalia Stakhanova University of Saskatchewan, Zadia Codabux University of Saskatchewan, Canada | ||
17:12 4mTalk | DATAR: A Dataset for Tracking App Releases Data and Tool Showcase Track Yasaman Abedini Sharif University of Technology, Mohammad Hadi Hajihosseini Sharif University of Technology, Abbas Heydarnoori Bowling Green State University | ||
17:16 4mTalk | AndroZoo: A Retrospective with a Glimpse into the Future Data and Tool Showcase Track Marco Alecci University of Luxembourg, Pedro Jesús Ruiz Jiménez University of Luxembourg, Kevin Allix Independent Researcher, Tegawendé F. Bissyandé University of Luxembourg, Jacques Klein University of Luxembourg | ||
16:00 - 17:30 | Machine learning for Software EngineeringTechnical Papers at Grande Auditório Chair(s): Diego Costa Concordia University, Canada | ||
16:00 12mTalk | Whodunit: Classifying Code as Human Authored or GPT-4 Generated - A case study on CodeChef problems Technical Papers Oseremen Joy Idialu University of Waterloo, Noble Saji Mathews University of Waterloo, Canada, Rungroj Maipradit University of Waterloo, Joanne M. Atlee University of Waterloo, Mei Nagappan University of Waterloo DOI Pre-print | ||
16:12 12mTalk | GIRT-Model: Automated Generation of Issue Report Templates Technical Papers Nafiseh Nikehgbal Sharif University of Technology, Amir Hossein Kargaran LMU Munich, Abbas Heydarnoori Bowling Green State University DOI Pre-print | ||
16:24 12mTalk | MicroRec: Leveraging Large Language Models for Microservice Recommendation Technical Papers Ahmed Saeed Alsayed University of Wollongong, Hoa Khanh Dam University of Wollongong, Chau Nguyen University of Wollongong | ||
16:36 12mTalk | PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software Technical Papers Wenxin Jiang Purdue University, Jerin Yasmin Queen's University, Canada, Jason Jones Purdue University, Nicholas Synovic Loyola University Chicago, Jiashen Kuo Purdue University, Nathaniel Bielanski Purdue University, Yuan Tian Queen's University, Kingston, Ontario, George K. Thiruvathukal Loyola University Chicago and Argonne National Laboratory, James C. Davis Purdue University DOI Pre-print | ||
16:48 12mTalk | Data Augmentation for Supervised Code Translation Learning Technical Papers Binger Chen Technische Universität Berlin, Jacek golebiowski Amazon AWS, Ziawasch Abedjan Leibniz Universität Hannover | ||
17:00 12mTalk | On the Effectiveness of Machine Learning-based Call-Graph Pruning: An Empirical Study Technical Papers Amir Mir Delft University of Technology, Mehdi Keshani Delft University of Technology, Sebastian Proksch Delft University of Technology Pre-print | ||
17:12 12mTalk | Leveraging GPT-like LLMs to Automate Issue Labeling Technical Papers Giuseppe Colavito University of Bari, Italy, Filippo Lanubile University of Bari, Nicole Novielli University of Bari, Luigi Quaranta University of Bari, Italy Pre-print | ||
Tue 16 AprDisplayed time zone: Lisbon change
09:00 - 10:30 | Development: practices and humans Data and Tool Showcase Track / Technical Papers at Almada Negreiros Chair(s): Gema Rodríguez-Pérez University of British Columbia (UBC) | ||
09:50 6mTalk | Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot Technical Papers Kei Koyanagi Kyushu University, Dong Wang Kyushu University, Japan, Kotaro Noguchi Kyushu University, Masanari Kondo Kyushu University, Alexander Serebrenik Eindhoven University of Technology, Yasutaka Kamei Kyushu University, Naoyasu Ubayashi Kyushu University Pre-print | ||
09:56 4mTalk | A Four-Dimension Gold Standard Dataset for Opinion Mining in Software Engineering Data and Tool Showcase Track Md Rakibul Islam Lamar University, Md Fazle Rabbi Idaho State University, Jo Youngeun Lamar University, Arifa Islam Champa Idaho State University, Ethan J Young Lamar University, Camden M Wilson Lamar University, Gavin J Scott Lamar University, Minhaz F. Zibran Idaho State University | ||
10:00 4mTalk | Opening the Valve on Pure-Data: Usage Patterns and Programming Practices of a Data-Flow Based Visual Programming Language Data and Tool Showcase Track Anisha Islam Department of Computing Science, University of Alberta, Kalvin Eng University of Alberta, Abram Hindle University of Alberta | ||
10:04 4mTalk | The PIPr Dataset of Public Infrastructure as Code Programs Data and Tool Showcase Track Daniel Sokolowski University of St. Gallen, David Spielmann University of St. Gallen, Guido Salvaneschi University of St. Gallen Link to publication DOI Pre-print | ||
10:08 4mTalk | A Dataset of Microservices-based Open-Source Projects Data and Tool Showcase Track Dario Amoroso d'Aragona Tampere University, Alexander Bakhtin University of Oulu, Xiaozhou Li University of Oulu, Ruoyu Su University of Oulu, Lauren Adams Baylor University, Ernesto Aponte Universidad del Sagrado Corazón, Francis Boyle Baylor University, Patrick Boyle Baylor University, Rachel Koerner Baylor University, Joseph Lee University of Richmond, Fangchao Tian University of Oulu, Yuqing Wang University of Oulu, Jesse Nyyssölä University of Helsinki, Ernesto Quevedo Baylor University, Shahidur Md Rahaman Baylor University, Amr Elsayed Baylor University, Mika Mäntylä University of Helsinki and University of Oulu, Tomas Cerny University of Arizona, Davide Taibi University of Oulu and Tampere University | ||
10:12 4mTalk | SensoDat: Simulation-based Sensor Dataset of Self-driving Cars Data and Tool Showcase Track Christian Birchler Zurich University of Applied Sciences & University of Bern, Cyrill Rohrbach University of Bern, Switzerland, Timo Kehrer University of Bern, Sebastiano Panichella Zurich University of Applied Sciences | ||
10:16 4mTalk | Incivility in Open Source Projects: A Comprehensive Annotated Dataset of Locked GitHub Issue Threads Data and Tool Showcase Track Ramtin Ehsani Drexel University, Mia Mohammad Imran Virginia Commonwealth University, Robert Zita Elmhurst University, Kostadin Damevski Virginia Commonwealth University, Preetha Chatterjee Drexel University, USA | ||
10:20 4mTalk | A Dataset of Atoms of Confusion in the Android Open Source Project Data and Tool Showcase Track Davi Batista Tabosa Federal University of Ceará, Oton Pinheiro Federal University of Ceará, Lincoln Rocha Federal University of Ceará, Windson Viana Federal University of Ceará | ||
10:24 4mTalk | PlayMyData: a curated dataset of multi-platform video games Data and Tool Showcase Track Andrea D'Angelo University of L'Aquila, Claudio Di Sipio University of L'Aquila, Cristiano Politowski DIRO, University of Montreal, Riccardo Rubei University of L'Aquila | ||
09:00 - 10:30 | |||
09:00 45mKeynote | Questioning the questions we ask about the impact of AI on software engineering Keynotes Margaret-Anne Storey University of Victoria | ||
09:45 45mTalk | Open Source Software Digital Sociology: Quantifying and Managing Complex Open Source Software Ecosystem Tutorials Minghui Zhou Peking University, Yuxia Zhang Beijing Institute of Technology, Xin Tan Beihang University | ||
11:00 - 12:30 | Process automation & DevOps and Tutorial ITechnical Papers / Tutorials at Almada Negreiros Chair(s): Tom Mens University of Mons, Ayushi Rastogi University of Groningen, The Netherlands | ||
11:00 12mTalk | Learning to Predict and Improve Build Successes in Package Ecosystems Technical Papers Harshitha Menon Lawrence Livermore National Lab, Daniel Nichols University of Maryland, College Park, Abhinav Bhatele University of Maryland, College Park, Todd Gamblin Lawrence Livermore National Laboratory | ||
11:12 12mTalk | The Impact of Code Ownership of DevOps Artefacts on the Outcome of DevOps CI Builds Technical Papers Ajiromola Kola-Olawuyi University of Waterloo, Nimmi Rashinika Weeraddana University of Waterloo, Mei Nagappan University of Waterloo | ||
11:24 12mTalk | A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase Technical Papers Zhili Zeng University of Waterloo, Tao Xiao Nara Institute of Science and Technology, Maxime Lamothe Polytechnique Montreal, Hideaki Hata Shinshu University, Shane McIntosh University of Waterloo Pre-print | ||
11:45 45mTalk | Cohort Studies for Mining Software Repositories Tutorials Nyyti Saarimäki Tampere University, Sira Vegas Universidad Politecnica de Madrid, Valentina Lenarduzzi University of Oulu, Davide Taibi University of Oulu and Tampere University , Mikel Robredo University of Oulu | ||
11:00 - 12:30 | Software Evolution & AnalysisTechnical Papers / Data and Tool Showcase Track / Industry Track at Grande Auditório Chair(s): Vladimir Kovalenko JetBrains Research | ||
11:00 12mTalk | Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based Study Technical Papers Rosalia Tufano Università della Svizzera Italiana, Antonio Mastropaolo Università della Svizzera italiana, Federica Pepe University of Sannio, Ozren Dabic Software Institute, Università della Svizzera italiana (USI), Switzerland, Massimiliano Di Penta University of Sannio, Italy, Gabriele Bavota Software Institute @ Università della Svizzera Italiana | ||
11:12 12mTalk | DRMiner: A Tool For Identifying And Analyzing Refactorings In Dockerfile Technical Papers Emna Ksontini University of Michigan - Dearborn, Aycha Abid Oakland University, Rania Khalsi University of Michigan - Flint, Marouane Kessentini University of Michigan - Flint | ||
11:24 12mTalk | A Large-Scale Empirical Study of Open Source License Usage: Practices and Challenges Technical Papers Jiaqi Wu Zhejiang University, Lingfeng Bao Zhejiang University, Xiaohu Yang Zhejiang University, Xin Xia Huawei Technologies, Xing Hu Zhejiang University | ||
11:36 12mTalk | Analyzing the Evolution and Maintenance of ML Models on Hugging Face Technical Papers Joel Castaño Fernández Universitat Politècnica de Catalunya, Silverio Martínez-Fernández UPC-BarcelonaTech, Xavier Franch Universitat Politècnica de Catalunya, Justus Bogner Vrije Universiteit Amsterdam Link to publication Pre-print | ||
11:48 12mTalk | On the Anatomy of Real-World R Code for Static Analysis Technical Papers Florian Sihler Ulm University, Lukas Pietzschmann Ulm University, Raphael Straub Ulm University, Matthias Tichy Ulm University, Germany, Andor Diera Ulm University, Abdelhalim Dahou GESIS Leibniz Institute for the Social Sciences Pre-print File Attached | ||
12:00 6mTalk | Encoding Version History Context for Better Code Representation Technical Papers Huy Nguyen The University of Melbourne, Christoph Treude Singapore Management University, Patanamon Thongtanunam University of Melbourne Pre-print | ||
12:06 4mTalk | CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code Data and Tool Showcase Track Martin Weyssow DIRO, Université de Montréal, Claudio Di Sipio University of L'Aquila, Davide Di Ruscio University of L'Aquila, Houari Sahraoui DIRO, Université de Montréal | ||
12:10 4mTalk | Bidirectional Paper-Repository Tracing in Software Engineering Data and Tool Showcase Track Daniel Garijo , Miguel Arroyo Universidad Politécnica de Madrid, Esteban González Guardia Universidad Politécnica de Madrid, Christoph Treude Singapore Management University, Nicola Tarocco CERN | ||
12:14 4mTalk | DistilKaggle: A Distilled Dataset of Kaggle Jupyter Notebooks Data and Tool Showcase Track Mojtaba Mostafavi Department of Computer Engineering of Sharif University of Technology, Arash Asgari Department of Computer Engineering of Sharif University of Technology, Mohammad Abolnejadian Department of Computer Engineering of Sharif University of Technology, Abbas Heydarnoori Bowling Green State University | ||
12:18 5mTalk | Estimating Usage of Open Source Projects Industry Track | ||
14:00 - 15:30 | Process automation & DevOps IITechnical Papers / Data and Tool Showcase Track at Almada Negreiros Chair(s): Shane McIntosh University of Waterloo | ||
14:00 12mTalk | Options Matter: Documenting and Fixing Non-Reproducible Builds in Highly-Configurable Systems Technical Papers Georges Aaron RANDRIANAINA Université de Rennes 1, IRISA, Djamel Eddine Khelladi CNRS, IRISA, University of Rennes, Olivier Zendra Inria, Mathieu Acher University of Rennes, France / Inria, France / CNRS, France / IRISA, France | ||
14:12 12mTalk | How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions Technical Papers João Helis Bernardo Federal Institute of Education, Science and Technology of Rio Grande do Norte, Daniel Alencar Da Costa University of Otago, Sergio Queiroz de Medeiros Universidade Federal do Rio Grande do Norte, Uirá Kulesza Federal University of Rio Grande do Norte DOI Pre-print | ||
14:24 4mTalk | A dataset of GitHub Actions workflow histories Data and Tool Showcase Track Guillaume Cardoen University of Mons, Tom Mens University of Mons, Alexandre Decan University of Mons; F.R.S.-FNRS | ||
14:28 4mTalk | gawd: A Differencing Tool for GitHub Actions Workflows Data and Tool Showcase Track Pooya Rostami Mazrae University of Mons, Alexandre Decan University of Mons; F.R.S.-FNRS, Tom Mens University of Mons | ||
14:32 4mTalk | RABBIT: A tool for identifying bot accounts based on their recent GitHub event history Data and Tool Showcase Track Natarajan Chidambaram University of Mons, Tom Mens University of Mons, Alexandre Decan University of Mons; F.R.S.-FNRS | ||
14:36 12mTalk | An Investigation of Patch Porting Practices of the Linux Kernel Ecosystem Technical Papers Xingyu Li UC Riverside, Zheng Zhang UC Riverside, Zhiyun Qian University of California at Riverside, USA, Trent Jaeger UC Riverside, Chengyu Song University of California at Riverside, USA | ||
14:48 4mTalk | BugsPHP: A dataset for Automated Program Repair in PHP Data and Tool Showcase Track K.D. Pramod University of Moratuwa, Sri Lanka, W.T.N. De Silva University of Moratuwa, Sri Lanka, W.U.K. Thabrew University of Moratuwa, Sri Lanka, Ridwan Salihin Shariffdeen National University of Singapore, Sandareka Wickramanayake University of Moratuwa, Sri Lanka Pre-print | ||
16:00 - 17:30 | Day 2: ClosingMSR Awards / Vision and Reflection at Grande Auditório Chair(s): Alberto Bacchelli University of Zurich | ||
16:00 30mTalk | MSR in the age of LLMs Vision and Reflection Christoph Treude Singapore Management University | ||
16:30 30mTalk | Idealists and Pragmatists—An Only Somewhat Self-Indulgent Reflection on the Development of an MSR Paper (and Researcher) Vision and Reflection Shane McIntosh University of Waterloo | ||
17:00 30mDay closing | Closing session MSR Awards Diomidis Spinellis Athens University of Economics and Business & Delft University of Technology, Olga Baysal | ||
Accepted Papers
Call for Mining Challenge Papers
Mining Challenge Presentation: https://github.com/NAIST-SE/DevGPT/files/12923358/2024.MSR.Challenge.pdf
Mining Challenge Video: https://youtu.be/0EhskEg7NxA?si=4DfrnxjT90mWnjVx
The emergence of large language models (LLMs) such as ChatGPT has disrupted the landscape of software development. Many studies are investigating the quality of responses generated by ChatGPT, the efficacy of various prompting techniques, and its comparative performance in programming contests, to name a few examples. Yet, we know very little about how ChatGPT is actually used by software developers.
This year, the mining challenge focuses on DevGPT, a curated dataset of developer-ChatGPT conversations that encompasses prompts with ChatGPT’s responses, including code snippets. This dataset is paired with corresponding software development artifacts, which range from source code, commits, issues, and pull requests to discussions and Hacker News threads. The purpose of DevGPT is to enable a comprehensive analysis of the context and implications of developer interactions with ChatGPT.
To create DevGPT, we leveraged a feature introduced by OpenAI in late May 2023, which allows users to share their interactions with ChatGPT through dedicated links. DevGPT is updated weekly by tracking mentions of ChatGPT sharing links on GitHub and Hacker News, starting from July 27, 2023. The snapshot 20230831 contains 2,891 shared ChatGPT links, sourced from 2,237 GitHub or Hacker News references.
Challenge
The challenge is open-ended: participants can choose the research questions that they find most interesting. Our suggestions include:
- What types of issues (bugs, feature requests, theoretical questions, etc.) do developers most commonly present to ChatGPT?
- Can we identify patterns in the prompts developers use when interacting with ChatGPT, and do these patterns correlate with the success of issue resolution?
- What is the typical structure of conversations between developers and ChatGPT? How many turns does it take on average to reach a conclusion?
- In instances where developers have incorporated the code provided by ChatGPT into their projects, to what extent do they modify this code prior to use, and what are the common types of modifications made?
- How does the code generated by ChatGPT for a given query compare to code that could be found for the same query on the internet (e.g., on Stack Overflow)?
- What types of quality issues (for example, as identified by linters) are common in the code generated by ChatGPT?
- How accurately can we predict the length of a conversation with ChatGPT based on the initial prompt and context provided?
- Can we reliably predict whether a developer’s issue will be resolved based on the initial conversation with ChatGPT?
- If developers were to rerun their prompts with ChatGPT now and/or with different settings, would they obtain the same results?
Participants may combine the DevGPT data with mentions of links to ChatGPT shared on other platforms or websites. Participants are encouraged to “bring their own data” (BYOD) by integrating the DevGPT data with information from other public, readily available sources. We urge participants to thoroughly consider the ethical implications arising from using the DevGPT data in conjunction with other data sources. Sharing or using personally identifiable information is strictly prohibited.
How to Participate in the Challenge
First, familiarize yourself with the DevGPT infrastructure:
- The details about the DevGPT infrastructure are provided in our GitHub repositories.
- The dataset can be downloaded from either GitHub or Zenodo.
Use the dataset to answer your research questions, and report your findings in a four-page challenge paper that you submit to our challenge. If your paper is accepted, present your results at MSR 2024 in Lisbon, Portugal!
You can also join the DevGPT community, get support and find others to collaborate with. To do so:
- Join the live tutorial in September.
- Create new issues or discussions for problems, questions, or suggestions: https://github.com/NAIST-SE/DevGPT
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.
To ensure clarity and consistency in research submissions:
- When detailing methodologies or presenting findings, authors should specify which snapshot/version of the DevGPT dataset was utilized.
- Given the continuous updates to the dataset, authors are reminded to be precise in their dataset references. This will help maintain transparency and ensure consistent replication of results.
All authors should use the official “ACM Primary Article Template”, as can be obtained from the ACM Proceedings Template page. LaTeX users should use the sigconf option, as well as the review (to produce line numbers for easy reference by the reviewers) and anonymous (omitting author names) options. To that end, the following LaTeX code can be placed at the start of the LaTeX document:
\documentclass[sigconf,review,anonymous]{acmart}
\acmConference[MSR 2024]{MSR '24: Proceedings of the 21st International Conference on Mining Software Repositories}{April 15–16, 2024}{Lisbon, Portugal}
Submissions to the Challenge Track can be made via the submission site by the submission deadline. We encourage authors to upload their paper info early (the PDF can be submitted later) to properly enter conflicts for anonymous reviewing. All submissions must adhere to the following requirements:
- Submissions must not exceed the page limit (4 pages plus 1 additional page of references). The page limit is strict, and it will not be possible to purchase additional pages at any point in the process (including after acceptance).
- Submissions must strictly conform to the ACM formatting instructions. Alterations of spacing, font size, and other changes that deviate from the instructions may result in desk rejection without further review.
- Submissions must not reveal the authors’ identities. The authors must make every effort to honor the double-anonymous review process. In particular, the authors’ names must be omitted from the submission and references to their prior work should be in the third person. Further advice, guidance, and explanation about the double-anonymous review process can be found in the Q&A page for ICSE 2024.
- Submissions should consider the ethical implications of the research conducted within a separate section before the conclusion.
- The official publication date is the date the proceedings are made available in the ACM or IEEE Digital Libraries. This date may be up to two weeks prior to the first day of the ICSE 2024. The official publication date affects the deadline for any patent filings related to published work.
- Purchases of additional pages in the proceedings are not allowed.
Any submission that does not comply with these requirements is likely to be desk rejected by the PC Chairs without further review. In addition, by submitting to the MSR Challenge Track, the authors acknowledge that they are aware of and agree to be bound by the following policies:
- The ACM Policy and Procedures on Plagiarism and the IEEE Plagiarism FAQ. In particular, papers submitted to MSR 2024 must not have been published elsewhere and must not be under review or submitted for review elsewhere whilst under consideration for MSR 2024. Contravention of this concurrent submission policy will be deemed a serious breach of scientific ethics, and appropriate action will be taken in all such cases (including immediate rejection and reporting of the incident to ACM/IEEE). To check for double submission and plagiarism issues, the chairs reserve the right to (1) share the list of submissions with the PC Chairs of other conferences with overlapping review periods and (2) use external plagiarism detection software, under contract to the ACM or IEEE, to detect violations of these policies.
- The authorship policy of the ACM and the authorship policy of the IEEE.
Upon notification of acceptance, all authors of accepted papers will be asked to fill a copyright form and will receive further instructions for preparing the camera-ready version of their papers. At least one author of each paper is expected to register and present the paper at the MSR 2024 conference. All accepted contributions will be published in the electronic proceedings of the conference.
This year’s mining challenge and the data can be cited as:
@inproceedings{
title={DevGPT: Studying Developer-ChatGPT Conversations},
author={Xiao, Tao and Treude, Christoph and Hata, Hideaki and Matsumoto, Kenichi},
year={2024},
booktitle={Proceedings of the International Conference on Mining Software Repositories (MSR 2024)},
}
A preprint is available online.
Submission Site
Papers must be submitted through HotCRP: https://msr2024-challenge.hotcrp.com/
Important Dates
- Live tutorial and Kick-off session: September 2023
- Abstract Deadline: Dec 7, 2023
- Paper Deadline: Dec 11, 2023
- Author Notification: Jan 19, 2024
- Camera Ready Deadline: Jan 28, 2024
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 DevGPT 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 anonymizing 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 anonymized. 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.
Call for Mining Challenge Proposals
Update: The MSR 24 Mining Challenge Paper is ‘‘DevGPT: Studying Developer-ChatGPT Conversations’’ by Tao Xiao, Christoph Treude, Hideaki Hata, and Kenichi Matsumoto!
DevGPT is a curated dataset which encompasses 16,129 prompts and ChatGPT’s responses including 9,785 code snippets, coupled with the corresponding software development artifacts—ranging from source code, commits, issues, pull requests, to discussions and Hacker News threads—to enable the analysis of the context and implications of these developer interactions with ChatGPT.
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.
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 2024 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 join the MSR 2024 organizing committee as Mining Challenge (co-)chair(s), who will manage the reviewing process (e.g., recruiting a Challenge PC, managing submissions and review assignments). Finally, it is not uncommon for challenge data sets to feature in MSR and other publications well after the edition of the conference in which they appear!
If you would like to submit your data set for consideration for the 2024 MSR Mining Challenge, please submit a short proposal (1-2 pages plus appendices, if needed) at https://msr-mc24.hotcrp.com/, containing the following information:
- Title of data set.
- High-level overview:
- Short description, including what types of artifacts the data set contains.
- Summary statistics (how many artifacts of different types).
- Internal structure:
- How are the data structured and organized?
- (Link to) Schema, if applicable
- How to access:
- How can the data set be obtained?
- What are recommended ways to access it? Include examples of specific tools, shell commands, etc, if applicable.
- What skills, infrastructure, and/or credentials would challenge participants need to effectively work with the data set?
- What kinds of research questions do you expect challenge participants could answer?
- A link to a (sub)sample of the data for the organizing committee to pursue (e.g., via GitHub, Zenodo, Figshare).
Each submission must 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
The first task of the authors of the selected proposal will be to prepare the Call for Challenge Papers, which outlines the expected content and structure of submissions, as well as the technical details of how to access and analyze the data set. This call will be published on the MSR website on September 1st. By making the challenge data set available by late summer, we hope that many students will be able to use the challenge data set for their graduate class projects in the Fall semester.
Important dates:
- Deadline for proposals: August 15, 2023
- Notification: August 24, 2023
- Call for Challenge Papers Published: September 1, 2023
Expected deadlines for Mining Challenge Papers:
- Live tutorial and Kick-off session: September 2023
- Abstract Deadline: Dec 7, 2023
- Paper Deadline: Dec 11, 2023
- Author Notification: Jan 19, 2024
- Camera Ready Deadline: Jan 28, 2024
| Mon 11 Dec 2023 Paper Deadline |
| Thu 7 Dec 2023 Abstract Deadline |
Preetha Chatterjee
Drexel University, USA
United States
Fabio Palomba
University of Salerno
Italy
Daniel Russo
Department of Computer Science, Aalborg University
Denmark
Peng Liang
Wuhan University, China
China
Tianyi Zhang
Purdue University
United States
Masanari Kondo
Kyushu University
Japan
Marcelo De Almeida Maia
Federal University of Uberlandia
Brazil
Kevin Moran
University of Central Florida
United States
Raula Gaikovina Kula
Nara Institute of Science and Technology
Japan
Fabio Calefato
University of Bari
Italy
Nathalia Nascimento
University of Waterloo
Canada
Maliheh Izadi
Delft University of Technology
Netherlands
Mahmoud Alfadel
University of Waterloo
Canada
Joanna C. S. Santos
University of Notre Dame
United States
Neil Ernst
University of Victoria
Canada
Hideaki Hata
Shinshu University
Japan
Takashi Ishio
Future University Hakodate
Japan
Mircea Lungu
IT University, Copenhagen
Kenichi Matsumoto
Nara Institute of Science and Technology
Yusuf Sulistyo Nugroho
Universitas Muhammadiyah Surakarta
Indonesia
Ali Ouni
ETS Montreal, University of Quebec
Canada
Banani Roy
University of Saskatchewan
Chanchal K. Roy
University of Saskatchewan, Canada
Canada
Yuan Tian
Queen's University, Kingston, Ontario
Canada
Christoph Treude
Singapore Management University
Singapore
Dong Wang
Kyushu University, Japan
Japan
Haoyu Wang
Huazhong University of Science and Technology
China
Tao Xiao
Nara Institute of Science and Technology
Japan