ICSE 2021 (series) / Technical Track / Restoring Execution Environments of Jupyter Notebooks
Restoring Execution Environments of Jupyter NotebooksTechnical Track
Wed 26 May 2021 11:20 - 11:40 at Blended Sessions Room 4 - 2.1.4. Tools for the Python Language Chair(s): Igor Steinmacher
Wed 26 May 2021 23:20 - 23:40 at Blended Sessions Room 4 - 2.1.4. Tools for the Python Language
Wed 26 May 2021 23:20 - 23:40 at Blended Sessions Room 4 - 2.1.4. Tools for the Python Language
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 scientific results. We present SnifferDog, an approach that 1) collects the APIs of Python packages and versions, creating a database of APIs; 2) analyzes notebooks to determine candidates for required packages and versions; and 3) checks which packages are required to make the notebook executable (and ideally, reproduce its stored results). In its evaluation, we show that SnifferDog precisely restores execution environments for the largest majority of notebooks, making them immediately executable for end users.
Wed 26 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
Wed 26 May
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:20 - 12:20 | 2.1.4. Tools for the Python LanguageTechnical Track at Blended Sessions Room 4 +12h Chair(s): Igor Steinmacher Northern Arizona University, USA | ||
11:20 20mResearch paper | Restoring Execution Environments of Jupyter NotebooksTechnical Track Technical Track Jiawei Wang Monash University, Li Li Monash University, Andreas Zeller CISPA Helmholtz Center for Information Security Pre-print Media Attached | ||
11:40 20mPaper | PyART: Python API Recommendation in Real-TimeTechnical Track Technical Track Xincheng He State Key Laboratory for Novel Software Technology, Nanjing University, Lei Xu State Key Laboratory for Novel Software Technology, Nanjing University, Xiangyu Zhang Purdue University, Rui Hao State Key Laboratory for Novel Software Technology Nanjing University, Yang Feng State Key Laboratory for Novel Software Technology, Nanjing University, Baowen Xu Nanjing University Pre-print Media Attached | ||
12:00 20mPaper | PyCG: Practical Call Graph Generation in PythonTechnical Track Technical Track Vitalis Salis Athens University of Economics and Business, National and Technical University of Athens, Thodoris Sotiropoulos Athens University of Economics and Business, Panos Louridas Athens University of Economics and Business, Diomidis Spinellis Athens University of Economics and Business & TU Delft, Dimitris Mitropoulos National and Kapodistrian University of Athens Pre-print Media Attached |
23:20 - 00:20 | |||
23:20 20mResearch paper | Restoring Execution Environments of Jupyter NotebooksTechnical Track Technical Track Jiawei Wang Monash University, Li Li Monash University, Andreas Zeller CISPA Helmholtz Center for Information Security Pre-print Media Attached | ||
23:40 20mPaper | PyART: Python API Recommendation in Real-TimeTechnical Track Technical Track Xincheng He State Key Laboratory for Novel Software Technology, Nanjing University, Lei Xu State Key Laboratory for Novel Software Technology, Nanjing University, Xiangyu Zhang Purdue University, Rui Hao State Key Laboratory for Novel Software Technology Nanjing University, Yang Feng State Key Laboratory for Novel Software Technology, Nanjing University, Baowen Xu Nanjing University Pre-print Media Attached | ||
00:00 20mPaper | PyCG: Practical Call Graph Generation in PythonTechnical Track Technical Track Vitalis Salis Athens University of Economics and Business, National and Technical University of Athens, Thodoris Sotiropoulos Athens University of Economics and Business, Panos Louridas Athens University of Economics and Business, Diomidis Spinellis Athens University of Economics and Business & TU Delft, Dimitris Mitropoulos National and Kapodistrian University of Athens Pre-print Media Attached |