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ICSE 2022
Sun 8 - Fri 27 May 2022
Tue 10 May 2022 20:00 - 20:05 at ICSE room 5-even hours - Configurations and Recommendations Chair(s): Candy Pang
Wed 11 May 2022 04:00 - 04:05 at ICSE room 3-even hours - Recommender Systems 1 Chair(s): Alessio Ferrari
Fri 27 May 2022 09:00 - 09:05 at Room 306+307 - Papers 18: Recommender Systems, tools and environments Chair(s): Christian Bird

Software repositories such as GitHub host a large number of software entities. Developers collaboratively discuss, implement, use, and share these entities. Proper documentation plays an important role in successful software management and maintenance. Users exploit Issue Tracking Systems, a facility of software repositories, to keep track of issue reports, to manage the workload and processes, and finally, to document the highlight of their team’s effort. An issue report is a rich source of collaboratively-curated software knowledge, and can contain a reported problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage them manually. GitHub provides labels for tagging issues, as a means of issue management. However, about half of the issues in GitHub’s top 1000 repositories do not have any labels. In this work, we aim at automating the process of managing issue reports for software teams. We propose a two-stage approach to predict both the objective behind opening an issue and its priority level using feature engineering methods and state-of-the-art text classifiers. To the best of our knowledge, we are the first to fine-tune a Transformer for issue classification. We train and evaluate our models in both project-based and cross-project settings. The latter approach provides a generic prediction model applicable for any unseen software project or projects with little historical data. Our proposed approach can successfully predict the objective and priority level of issue reports with 82% (fine-tuned RoBERTa) and 75% (Random Forest) accuracy, respectively. Moreover, we conducted human labeling and evaluation on unlabeled issues from six unseen GitHub projects to assess the performance of the cross-project model on new data. The model achieves 90% accuracy on the sample set. We measure inter-rater reliability and obtain an average Percent Agreement of 85.3% and Randolph’s free-marginal Kappa of 0.71 that translate to a substantial agreement among labelers.

Tue 10 May

Displayed time zone: Eastern Time (US & Canada) change

20:00 - 21:00
20:00
5m
Talk
Predicting the Objective and Priority of Issue Reports in Software Repositories
Journal-First Papers
Maliheh Izadi Sharif University of Technology, Kiana Akbari Sharif University of technology, Abbas Heydarnoori Sharif University of Technology
Link to publication DOI Pre-print Media Attached
20:05
5m
Talk
Better Modeling the Programming World with Code Concept Graphs-augmented Multi-modal Learning
NIER - New Ideas and Emerging Results
Martin Weyssow DIRO, Université de Montréal, Houari Sahraoui Université de Montréal, Bang Liu DIRO & Mila, Université de Montréal
Pre-print Media Attached
20:10
5m
Talk
Dozer: Migrating Shell Commands to Ansible Modules via Execution Profiling and Synthesis
SEIP - Software Engineering in Practice
Eric Horton North Carolina State University, Chris Parnin North Carolina State University
Pre-print Media Attached
20:15
5m
Talk
Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph
Technical Track
Wei Cheng Nanjing University, XiangRong Zhu Nanjing University, Wei Hu Nanjing University
DOI Pre-print Media Attached
20:20
5m
Talk
CLEAR: Contrastive Learning for API Recommendation
Technical Track
Moshi Wei York University, Nima Shiri harzevili York University, Yuchao Huang Institute of Software Chinese Academy of Sciences, Junjie Wang Institute of Software at Chinese Academy of Sciences, Song Wang York University
Pre-print Media Attached

Wed 11 May

Displayed time zone: Eastern Time (US & Canada) change

04:00 - 05:00
04:00
5m
Talk
Predicting the Objective and Priority of Issue Reports in Software Repositories
Journal-First Papers
Maliheh Izadi Sharif University of Technology, Kiana Akbari Sharif University of technology, Abbas Heydarnoori Sharif University of Technology
Link to publication DOI Pre-print Media Attached
04:05
5m
Talk
Code Reviewer Recommendation in Tencent: Practice, Challenge, and Direction
SEIP - Software Engineering in Practice
Qiuyuan Chen Zhejiang University, Dezhen Kong Zhejiang University, Lingfeng Bao Zhejiang University, Chenxing Sun Tencent, Xin Xia Huawei Software Engineering Application Technology Lab, Shanping Li Zhejiang University
Pre-print Media Attached
04:10
5m
Talk
Using Deep Learning to Generate Complete Log Statements
Technical Track
Antonio Mastropaolo Università della Svizzera italiana, Luca Pascarella Università della Svizzera italiana (USI), Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print Media Attached
04:15
5m
Talk
Modeling Review History for Reviewer Recommendation: A Hypergraph Approach
Technical Track
Guoping Rong Nanjing University, YiFan Zhang Nanjing University, Lanxin Yang Nanjing University, Fuli Zhang Nanjing University, Hongyu Kuang Nanjing University, He Zhang Nanjing University
Pre-print Media Attached
04:20
5m
Talk
ShellFusion: Answer Generation for Shell Programming Tasks via Knowledge Fusion
Technical Track
Neng Zhang School of Software Engineering, Sun Yat-sen University, Chao Liu Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, Christoph Treude University of Melbourne, Ying Zou Queen's University, Kingston, Ontario, David Lo Singapore Management University, Zibin Zheng School of Data and Computer Science, Sun Yat-sen University
DOI Pre-print Media Attached
04:25
5m
Talk
CLEAR: Contrastive Learning for API Recommendation
Technical Track
Moshi Wei York University, Nima Shiri harzevili York University, Yuchao Huang Institute of Software Chinese Academy of Sciences, Junjie Wang Institute of Software at Chinese Academy of Sciences, Song Wang York University
Pre-print Media Attached

Fri 27 May

Displayed time zone: Eastern Time (US & Canada) change

09:00 - 10:30
Papers 18: Recommender Systems, tools and environmentsTechnical Track / Journal-First Papers / NIER - New Ideas and Emerging Results / SEIP - Software Engineering in Practice at Room 306+307
Chair(s): Christian Bird Microsoft Research
09:00
5m
Talk
Predicting the Objective and Priority of Issue Reports in Software Repositories
Journal-First Papers
Maliheh Izadi Sharif University of Technology, Kiana Akbari Sharif University of technology, Abbas Heydarnoori Sharif University of Technology
Link to publication DOI Pre-print Media Attached
09:05
5m
Talk
Using Deep Learning to Generate Complete Log Statements
Technical Track
Antonio Mastropaolo Università della Svizzera italiana, Luca Pascarella Università della Svizzera italiana (USI), Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print Media Attached
09:10
5m
Talk
Better Modeling the Programming World with Code Concept Graphs-augmented Multi-modal Learning
NIER - New Ideas and Emerging Results
Martin Weyssow DIRO, Université de Montréal, Houari Sahraoui Université de Montréal, Bang Liu DIRO & Mila, Université de Montréal
Pre-print Media Attached
09:15
5m
Talk
"Project smells" — Experiences in Analysing the Software Quality of ML Projects with mllint
SEIP - Software Engineering in Practice
Bart van Oort Delft University of Technology, Luís Cruz Deflt University of Technology, Babak Loni ING Bank N.V., Arie van Deursen Delft University of Technology, Netherlands
Pre-print Media Attached
09:20
5m
Talk
Discovering Repetitive Code Changes in Python ML Systems
Technical Track
Malinda Dilhara University of Colorado Boulder, USA, Ameya Ketkar Oregon State University, USA, Nikhith Sannidhi University of Colorado Boulder, Danny Dig University of Colorado Boulder, USA
DOI Pre-print Media Attached
09:25
5m
Talk
FlakiMe: Laboratory-Controlled Test Flakiness Impact Assessment
Technical Track
Maxime Cordy University of Luxembourg, Luxembourg, Renaud Rwemalika University of Luxembourg, Adriano Franci University of Luxembourg, Mike Papadakis University of Luxembourg, Luxembourg, Mark Harman University College London
Pre-print Media Attached
09:30
5m
Talk
Semantic Image Fuzzing of AI Perception Systems
Technical Track
Trey Woodlief University of Virginia, Sebastian Elbaum University of Virginia, Kevin Sullivan University of Virginia
DOI Pre-print Media Attached
09:35
5m
Talk
Understanding and improving artifact sharing in software engineering research
Journal-First Papers
Christopher Steven Timperley Carnegie Mellon University, Lauren Herckis Carnegie Mellon University, Claire Le Goues Carnegie Mellon University, Michael Hilton Carnegie Mellon University, USA
Link to publication DOI Pre-print Media Attached
09:40
5m
Talk
ARCLIN: Automated API Mention Resolution for Unformatted Texts
Technical Track
Yintong Huo The Chinese University of Hong Kong, Yuxin Su Sun Yat-sen University, Hongming Zhang The Hong Kong University of Science and Technology, Michael Lyu The Chinese University of Hong Kong
DOI Pre-print Media Attached

Information for Participants
Tue 10 May 2022 20:00 - 21:00 at ICSE room 5-even hours - Configurations and Recommendations Chair(s): Candy Pang
Info for room ICSE room 5-even hours:

Click here to go to the room on Midspace

Wed 11 May 2022 04:00 - 05:00 at ICSE room 3-even hours - Recommender Systems 1 Chair(s): Alessio Ferrari
Info for room ICSE room 3-even hours:

Click here to go to the room on Midspace