activity
20192023
most citedBetter Code, Better Sharing:On the Need of Analyzing Jupyter Notebooks

8 citations · 13 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2023

Static Analysis Driven Enhancements for Comprehension in Machine Learning Notebooks

Ashwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Mouli Chekkapalli +3

Jupyter notebooks enable developers to interleave code snippets with rich-text and in-line visualizations. Data scientists use Jupyter notebook as the de-facto standard for creatin…

cs.PL2022★ 2 cited

CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training

Xin Wang, Yasheng Wang, Yao Wan +5

Recent years have witnessed increasing interest in code representation learning, which aims to represent the semantics of source code into distributed vectors. Currently, various w…

cs.SE2022

Scalpel: The Python Static Analysis Framework

Li Li, Jiawei Wang, Haowei Quan

Despite being the most popular programming language, Python has not yet received enough attention from the community. To the best of our knowledge, there is no general static analy…

cs.SE2021★ 3 cited

Restoring Execution Environments of Jupyter Notebooks

Jiawei Wang, Li Li, Andreas Zeller

More than ninety percent of published Jupyter notebooks do not state dependencies on external packages. This makes them non-executable and thus hinders reproducibility of scientifi…

cs.SE2019★ 8 cited

Better Code, Better Sharing:On the Need of Analyzing Jupyter Notebooks

Jiawei Wang, Li Li, Andreas Zeller

By bringing together code, text, and examples, Jupyter notebooks have become one of the most popular means to produce scientific results in a productive and reproducible way. As ma…