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14th International Conference on Graph Transformation (ICGT) Held as Part of Conference on Software Technologies - Applications and Foundations (STAF)

作者： Weber, Jens H. Univ Victoria Victoria BC Canada

ISBN: (纸本)9783030789466;9783030789459

computational notebooks (CNs) have gained popularity in data science, artificial intelligence, and engineering. CNs are used to document experiments and make them repeatable by incorporating executable segments and renderings of computational results. Graphs and computations by graph transformations have applications in many problem domains but they are not supported by current CNs. Existing graph transformation tools require a steep learning curve and are not integrated with CNs. In order to close this gap, we have developed GrapePress a CN that incorporates graphs and computations by graph transformations. We present the fundamental concepts for GrapePress and describe its use in documenting executable experiments involving graph transformations to approach real world problems in science and engineering.

关键词： Graph transformations computational notebook Tools

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Predicting the understandability of computational notebooks through code metrics analysis

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EMPIRICAL SOFTWARE ENGINEERING 2025年第3期30卷 1-43页

作者： Ghahfarokhi, Mojtaba Mostafavi Asadi, Alireza Asgari, Arash Mohammadi, Bardia Heydarnoori, Abbas Sharif Univ Technol Dept Comp Engn Tehran Iran York Univ Vector Inst AI Dept Comp Sci Toronto ON Canada

computational notebooks have become the primary coding environment for data scientists. Despite their popularity, research on the code quality of these notebooks is still in its infancy, and the code shared in these notebooks is often of poor quality. Considering the importance of maintenance and reusability, it is crucial to pay attention to the understandability of the notebook code and identify the notebook metrics that play a significant role in its understandability. The level of code understandability is a qualitative variable closely associated with the user's opinion about the code. Traditional approaches to measuring it either use limited questionnaires to review a few code pieces or rely on metadata such as likes and votes in software repositories. In our approach, we enhanced the measurement of the understandability level of Jupyter notebooks by leveraging user opinions related to code understandability within a software repository. As a case study, we started with 542,051 Kaggle Jupyter notebooks, compiled in a dataset named DistilKaggle, which we introduced in our previous research. To identify user comments associated with code understandability, we utilized a fine-tuned DistilBERT transformer. We established a user-opinion-based criterion for measuring code understandability by considering the number of code understandability-related comments, the upvotes on those comments and the total views of the notebook received by the notebook. We refer to this criterion as User Opinion Code Understandability (UOCU), which has been proven to be much more effective than previous approaches. A hybrid approach combining UOCU with total upvotes further improved this criterion. Additionally, we trained machine learning models to classify notebook understandability solely based on notebook metrics. We collected 34 metrics for 132,723 final notebooks using the hybrid approach criterion. Our predictive model, built using a Random Forest classifier, achieved 89% accuracy

关键词： computational notebook Code understandability Kaggle Jupyter notebook metrics Machine learning

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InterLink: Linking Text with Code and Output in computational notebooks 25

InterLink: Linking Text with Code and Output in Computationa...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Yanna Lin Leni Yang Haotian Li Huamin Qu Dominik Moritz Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China and Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh Pennsylvania USA Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China Microsoft Research Asia Beijing China Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh Pennsylvania USA

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Remote Labs Meet computational notebooks: An Architecture for Simplifying the Workflow of Remote Educational Experiments

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IEEE ACCESS 2023年 11卷 132496-132515页

作者： Vanegas-Guillen, Oswaldo Parra-Rosero, Pablo Munoz-Anton, Javier Mu Zumba-Gamboa, Johanna Dillon, Carlos Tech Univ Madrid Sch Ind Engn Dept Energy Engn Madrid 28006 Spain Univ Guayaquil Fac Math & Phys Sci Dept Informat Technol Guayaquil 090514 Ecuador Univ Politecn Salesiana Res Grp Ind Proc GIPI Guayaquil 090101 Ecuador Univ Guayaquil Fac Math & Phys Sci Dept Computat Syst Guayaquil 090514 Ecuador Univ Politecn Salesiana Dept Comp Sci Guayaquil 090101 Ecuador

Online laboratories and computational notebooks have established themselves as essential tools in the fields of engineering and science education, significantly enhancing the teaching and learning experience. Despite the benefits of remote laboratories, and although architectures, models, and tools have been proposed to facilitate the work involved in their implementation, challenges remain in the development lifecycle. This paper proposes a novel architecture that simplifies the development and management of remote experiments using a publisher-subscriber communication paradigm to securely and efficiently integrate WebAssembly computational notebooks. This approach eliminates the need for additional infrastructure for communication at the lab stations. It also avoids the need for servers to deploy notebooks, because all operations, calculations, and data processing run locally in the user's web browser. To achieve this, a remote laboratory management system (RLMS) interoperable with virtual learning environments was designed and implemented, including notebook-based authoring, learning scenarios, and grading tools. As a case study, remote experiments were developed to characterize and evaluate the performance of heat exchangers using a thermal fluid systems test bench built for this project. Several quality criteria categorized into technical, educational, and adaptability groups were quantitatively evaluated using the responses of 70 participants from two different universities. The analysis highlighted both the advantages and challenges of the proposal, with a significant emphasis on interaction, scalability, reusability, interoperability, and accessibility. The results confirmed the effectiveness of the notebooks in each phase of the remote experiments, demonstrating an increase in students' active and autonomous participation and exploration.

关键词： Architecture computational notebook engineering education online experimentation online laboratory remote laboratory thermal fluids

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InkSight: Leveraging Sketch Interaction for Documenting Chart Findings in computational notebooks

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第1期30卷 944-954页

作者： Lin, Yanna Li, Haotian Yang, Leni Wu, Aoyu Qu, Huamin Hong Kong Univ Sci & Technol Hong Kong Peoples R China Harvard Univ Cambridge MA USA

computational notebooks have become increasingly popular for exploratory data analysis due to their ability to support data exploration and explanation within a single document. Effective documentation for explaining chart findings during the exploration process is essential as it helps recall and share data analysis. However, documenting chart findings remains a challenge due to its time-consuming and tedious nature. While existing automatic methods alleviate some of the burden on users, they often fail to cater to users' specific interests. In response to these limitations, we present InkSight, a mixed-initiative computational notebook plugin that generates finding documentation based on the user's intent. InkSight allows users to express their intent in specific data subsets through sketching atop visualizations intuitively. To facilitate this, we designed two types of sketches, i.e., open-path and closed-path sketch. Upon receiving a user's sketch, InkSight identifies the sketch type and corresponding selected data items. Subsequently, it filters data fact types based on the sketch and selected data items before employing existing automatic data fact recommendation algorithms to infer data facts. Using large language models (GPT-3.5), InkSight converts data facts into effective natural language documentation. Users can conveniently fine-tune the generated documentation within InkSight. A user study with 12 participants demonstrated the usability and effectiveness of InkSight in expressing user intent and facilitating chart finding documentation.

关键词： Data visualization Documentation Data analysis Visualization Codes Natural languages Data models computational notebook Sketch-based Interaction Exploratory Data Analysis

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computational notebooks to support developers in prototyping IoT systems

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES 2022年 165卷

作者： Corno, Fulvio De Russis, Luigi Saenz, Juan Pablo Politecn Torino Dept Control & Comp Engn I-10129 Turin Italy

computational notebooks create narratives that consolidate text, executable code, and visualizations in a single document. They are widely used in data science, enabling data scientists to accurately document and execute the steps of their analyses in an exploratory and iterative manner. Prototyping Internet of Things (IoT) systems is also complex because of IoT heterogeneous and interconnected nature. Indeed, IoT system prototyping spans multiple development and execution environments, and developers, besides focusing on the code, are required to configure various devices. To ascertain if and how computational notebooks' capabilities might be useful in the IoT scenario, this work presents an IoT-tailored notebook architecture aimed at helping developers build and share a computational narrative around the prototyping of IoT systems. To that end, we propose the concept of "IoT notebook", for which we analyze the required features and present its first implementation. We evaluate our proposal by conducting an exploratory user study among non-expert IoT developers working in a large IT company. Finally, we point out the potential of this approach.

关键词： Internet of Things computational notebook Software development Prototyping

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Telling Stories from computational notebooks: AI-Assisted Presentation Slides Creation for Presenting Data ScienceWork 22

Telling Stories from Computational Notebooks: AI-Assisted Pr...

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Zheng, Chengbo Wang, Dakuo Wang, April Yi Ma, Xiaojuan Hong Kong Univ Sci & Technol Hong Kong Peoples R China IBM Res Cambridge MA USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA

ISBN: (纸本)9781450391573

Creating presentation slides is a critical but time-consuming task for data scientists. While researchers have proposed many AI techniques to lift data scientists' burden on data preparation and model selection, few have targeted the presentation creation task. Based on the needs identifed from a formative study, this paper presents NB2Slides, an AI system that facilitates users to compose presentations of their data science work. NB2Slides uses deep learning methods as well as example-based prompts to generate slides from computational notebooks, and take users' input (e.g., audience background) to structure the slides. NB2Slides also provides an interactive visualization that links the slides with the notebook to help users further edit the slides. A follow-up user evaluation with 12 data scientists shows that participants believed NB2Slides can improve efciency and reduces the complexity of creating slides. Yet, participants questioned the future of full automation and suggested a human-AI collaboration paradigm.

关键词： slides generation computational notebook

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SUPERNOVA: Design Strategies and Opportunities for Interactive Visualization in computational notebooks

SUPERNOVA: Design Strategies and Opportunities for Interacti...

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CHI Conference on Human Factors in Computing Sytems (CHI)

作者： Wang, Zijie J. Munechika, David Lee, Seongmin Chau, Duen Horng Georgia Tech Atlanta GA 30332 USA

ISBN: (纸本)9798400703317

computational notebooks, such as Jupyter notebook, have become data scientists' de facto programming environments. Many visualization researchers and practitioners have developed interactive visualization tools that support notebooks, yet little is known about the appropriate design of these tools. To address this critical research gap, we investigate the design strategies in this space by analyzing 163 notebook visualization tools. Our analysis encompasses 64 systems from academic papers and 105 systems sourced from a pool of 55k notebooks containing interactive visualizations that we obtain via scraping 8.6 million notebooks on GitHub. Through this study, we identify key design implications and trade-offs, such as leveraging multimodal data in notebooks as well as balancing the degree of visualization-notebook integration. Furthermore, we provide empirical evidence that tools compatible with more notebook platforms have a greater impact. Finally, we develop SuperNOVA, an open-source interactive browser to help researchers explore existing notebook visualization tools. SuperNOVA is publicly accessible at: https://***/supernova/.

关键词： computational notebook Interactive Visualization Systematic Review Data Science Design Cross-Platform Visualization

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Exploration and Explanation in computational notebooks

Exploration and Explanation in Computational Notebooks

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Rule, Adam Tabard, Aurelien Hollan, James D. Univ Calif San Diego Design Lab La Jolla CA 92093 USA Univ Lyon CNRS LIRIS UMR5205 Lyon France

ISBN: (纸本)9781450356206

computational notebooks combine code, visualizations, and text in a single document. Researchers, data analysts, and even journalists are rapidly adopting this new medium. We present three studies of how they are using notebooks to document and share exploratory data analyses. In the first, we analyzed over 1 million computational notebooks on GitHub, finding that one in four had no explanatoiy text but consisted entirely of visualizations or code. In a second study, we examined over 200 academic computational notebooks, finding that although the vast majority described methods, only a minority discussed reasoning or results. In a third study, we interviewed 15 academic data analysts, finding that most considered computational notebooks personal, exploratory, and messy. Importantly, they typically used other media to share analyses. These studies demonstrate a tension between exploration and explanation in constructing and sharing computational notebooks. We conclude with opportunities to encourage explanation in computational media without hindering exploration.

关键词： computational notebook Jupyter notebook data science data analysis narrative

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Towards computational notebooks for IoT Development

Towards Computational Notebooks for IoT Development

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Corno, Fulvio De Russis, Luigi Saenz, Juan Pablo Politecn Torino Turin Italy

ISBN: (纸本)9781450359719

Internet of Things systems are complex to develop. They are required to exhibit various features and run across several environments. Software developers have to deal with this heterogeneity both when configuring the development and execution environments and when writing the code. Meanwhile, computational notebooks have been gaining prominence due to their capability to consolidate text, executable code, and visualizations in a single document. Although they are mainly used in the field of data science, the characteristics of such notebooks could make them suitable to support the development of IoT systems as well. This work proposes an IoT-tailored literate computing approach in the form of a computational notebook. We present a use case of a typical IoT system involving several interconnected components and describe the implementation of a computational notebook as a tool to support its development. Finally, we point out the opportunities and limitations of this approach.

关键词： Internet of Things computational notebook Documentation Software development

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