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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia
Fri 19 May 2023 14:45 - 14:52 at Meeting Room 104 - Software development tools Chair(s): Xing Hu

A code context model consists of code elements and their relations relevant to a development task. Previous studies found that the explicit formation of code context models can benefit software development practices, e.g., code navigation and searching. However, little focus has been put on how to proactively form code context models. In this paper, we propose a tool named \textsc{Task Context} for predicting code context models and implement it as an Eclipse plug-in. \textsc{Task Context} uses the abstract topological patterns of how developers investigate structurally connected code elements when performing tasks. The tool captures the code elements navigated and searched by a developer to construct an initial code context model. The tool then applies abstract topological patterns with the initial code context model as input and recommends code elements up to 3 steps away in the code structure from the initial code context model. The experimental results indicate that our approach can predict code context models effectively, with a significantly higher F-measure than the state-of-the-art (0.57 over 0.23 on average). Furthermore, the user study suggests that our tool can help practitioners complete development tasks faster and more often as compared to standard Eclipse mechanism.

Demo video: https://youtu.be/3yEPh6uvHI8

Repository: https://github.com/icsoft-zju/Task_Context

Fri 19 May

Displayed time zone: Hobart change

13:45 - 15:15
13:45
15m
Talk
Safe low-level code without overhead is practical
Technical Track
Pre-print
14:00
15m
Talk
Sibyl: Improving Software Engineering Tools with SMT SelectionDistinguished Paper Award
Technical Track
Will Leeson University of Virgina, Matthew B Dwyer University of Virginia, Antonio Filieri AWS and Imperial College London
Pre-print
14:15
15m
Talk
Make Your Tools Sparkle with Trust: The PICSE Framework for Trust in Software Tools
SEIP - Software Engineering in Practice
Brittany Johnson George Mason University, Christian Bird Microsoft Research, Denae Ford Microsoft Research, Nicole Forsgren Microsoft Research, Thomas Zimmermann Microsoft Research
Pre-print
14:30
15m
Talk
CoCoSoDa: Effective Contrastive Learning for Code Search
Technical Track
Ensheng Shi Xi'an Jiaotong University, Wenchao Gu The Chinese University of Hong Kong, Yanlin Wang School of Software Engineering, Sun Yat-sen University, Lun Du Microsoft Research Asia, Hongyu Zhang The University of Newcastle, Shi Han Microsoft Research, Dongmei Zhang Microsoft Research, Hongbin Sun Xi'an Jiaotong University
Pre-print
14:45
7m
Talk
Task Context: A Tool for Predicting Code Context Models for Software Development Tasks
DEMO - Demonstrations
Yifeng Wang Zhejiang University, Yuhang Lin Zhejiang University, Zhiyuan Wan Zhejiang University, Xiaohu Yang Zhejiang University
Pre-print Media Attached
14:52
7m
Talk
Continuously Accelerating Research
NIER - New Ideas and Emerging Results
Sergey Mechtaev University College London, Jonathan Bell Northeastern University, Christopher Steven Timperley Carnegie Mellon University, Earl T. Barr University College London, Michael Hilton Carnegie Mellon University
Pre-print
15:00
7m
Talk
An Alternative to Cells for Selective Execution of Data Science Pipelines
NIER - New Ideas and Emerging Results
Lars Reimann University of Bonn, Günter Kniesel-Wünsche University of Bonn
Pre-print
15:07
7m
Talk
pytest-inline: An Inline Testing Tool for Python
DEMO - Demonstrations
Yu Liu University of Texas at Austin, Zachary Thurston Cornell University, Alan Han Cornell University, Pengyu Nie University of Texas at Austin, Milos Gligoric University of Texas at Austin, Owolabi Legunsen Cornell University