Scientific research is faces a software crisis. Software powers experimentation, and fuels insights, yielding new scientific contributions. Yet, the research software that we develop is often difficult for other researchers to reproducibly run. Even if research results can be reproduced, creating research software that is truly reusable, and can be easily extended by other researchers. As software engineering researchers, we believe that it is our duty to create tools and processes to instill these qualities of reusability and reproducibility in research software throughout the development process. This paper outlines a vision for a community infrastructure that will bring the benefits of continuous integration to scientists developing research software. This approach will appeal to researcher’s intrinsic self-motivations by making it easier to develop and evaluate research prototypes. This is a complex socio-technical problem that requires stakeholders to join forces to solve this problem for the software engineering community, and the greater scientific community as a whole. This vision paper outlines an agenda to realize a world where the reproducibility and reusability barriers in research software are lifted, continuously accelerating research.
Fri 19 MayDisplayed time zone: Hobart change
13:45 - 15:15 | Software development toolsDEMO - Demonstrations / Technical Track / SEIP - Software Engineering in Practice / NIER - New Ideas and Emerging Results at Meeting Room 104 Chair(s): Xing Hu Zhejiang University | ||
13:45 15mTalk | Safe low-level code without overhead is practical Technical Track Pre-print | ||
14:00 15mTalk | Sibyl: Improving Software Engineering Tools with SMT Selection Technical Track Will Leeson University of Virgina, Matthew B Dwyer University of Virginia, Antonio Filieri AWS and Imperial College London Pre-print | ||
14:15 15mTalk | 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 15mTalk | 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 7mTalk | 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 7mTalk | 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 7mTalk | An Alternative to Cells for Selective Execution of Data Science Pipelines NIER - New Ideas and Emerging Results Pre-print | ||
15:07 7mTalk | 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 | ||