Evolving the Computational Notebook: A Two-Dimensional Canvas for Enhanced Human-AI Interaction
Fuente:
arXiv
Saved in:
| Main Authors: | Grotov, Konstantin, Botov, Dmitry |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hidden Gems in the Rough: Computational Notebooks as an Uncharted Oasis for IDEs
by: Titov, Sergey, et al.
Published: (2024)
by: Titov, Sergey, et al.
Published: (2024)
Untangling Knots: Leveraging LLM for Error Resolution in Computational Notebooks
by: Grotov, Konstantin, et al.
Published: (2024)
by: Grotov, Konstantin, et al.
Published: (2024)
Observing Fine-Grained Changes in Jupyter Notebooks During Development Time
by: Titov, Sergey, et al.
Published: (2025)
by: Titov, Sergey, et al.
Published: (2025)
Themisto: Jupyter-Based Runtime Benchmark
by: Grotov, Konstantin, et al.
Published: (2025)
by: Grotov, Konstantin, et al.
Published: (2025)
Human to Document, AI to Code: Comparing GenAI for Notebook Competitions
by: Settewong, Tasha, et al.
Published: (2025)
by: Settewong, Tasha, et al.
Published: (2025)
A Study of Scientific Computational Notebook Quality
by: Kashiwa, Shun, et al.
Published: (2026)
by: Kashiwa, Shun, et al.
Published: (2026)
Are the Majority of Public Computational Notebooks Pathologically Non-Executable?
by: Nguyen, Tien, et al.
Published: (2025)
by: Nguyen, Tien, et al.
Published: (2025)
Integrating Code Metrics into Automated Documentation Generation for Computational Notebooks
by: Ghahfarokhi, Mojtaba Mostafavi, et al.
Published: (2026)
by: Ghahfarokhi, Mojtaba Mostafavi, et al.
Published: (2026)
Similarity-Based Assessment of Computational Reproducibility in Jupyter Notebooks
by: Hossain, A S M Shahadat, et al.
Published: (2025)
by: Hossain, A S M Shahadat, et al.
Published: (2025)
The Agentic Automation Canvas: a structured framework for agentic AI project design
by: Lobentanzer, Sebastian
Published: (2026)
by: Lobentanzer, Sebastian
Published: (2026)
PIPer: On-Device Environment Setup via Online Reinforcement Learning
by: Kovrigin, Alexander, et al.
Published: (2025)
by: Kovrigin, Alexander, et al.
Published: (2025)
Why do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks
by: Wang, Yiran, et al.
Published: (2024)
by: Wang, Yiran, et al.
Published: (2024)
A Taxonomy of Testable HTML5 Canvas Issues
by: Macklon, Finlay, et al.
Published: (2022)
by: Macklon, Finlay, et al.
Published: (2022)
Kernel-FFI: Transparent Foreign Function Interfaces for Interactive Notebooks
by: Li, Hebi, et al.
Published: (2025)
by: Li, Hebi, et al.
Published: (2025)
Predicting the Understandability of Computational Notebooks through Code Metrics Analysis
by: Ghahfarokhi, Mojtaba Mostafavi, et al.
Published: (2024)
by: Ghahfarokhi, Mojtaba Mostafavi, et al.
Published: (2024)
Method Names in Jupyter Notebooks: An Exploratory Study
by: Wong, Carol, et al.
Published: (2025)
by: Wong, Carol, et al.
Published: (2025)
Contextualized Data-Wrangling Code Generation in Computational Notebooks
by: Huang, Junjie, et al.
Published: (2024)
by: Huang, Junjie, et al.
Published: (2024)
Understanding Feedback Mechanisms in Machine Learning Jupyter Notebooks
by: Shome, Arumoy, et al.
Published: (2024)
by: Shome, Arumoy, et al.
Published: (2024)
Mining the Characteristics of Jupyter Notebooks in Data Science Projects
by: Choetkiertikul, Morakot, et al.
Published: (2023)
by: Choetkiertikul, Morakot, et al.
Published: (2023)
Now's the Time: Computer Science Must Evolve to Emphasize Software and Systems Engineering with Artificial Intelligence (AI)
by: Sekharan, Chandra N., et al.
Published: (2026)
by: Sekharan, Chandra N., et al.
Published: (2026)
Runtime-Augmented LLMs for Crash Detection and Diagnosis in ML Notebooks
by: Wang, Yiran, et al.
Published: (2026)
by: Wang, Yiran, et al.
Published: (2026)
Static Analysis Driven Enhancements for Comprehension in Machine Learning Notebooks
by: Venkatesh, Ashwin Prasad Shivarpatna, et al.
Published: (2023)
by: Venkatesh, Ashwin Prasad Shivarpatna, et al.
Published: (2023)
Typhon: Automatic Recommendation of Relevant Code Cells in Jupyter Notebooks
by: Ragkhitwetsagul, Chaiyong, et al.
Published: (2024)
by: Ragkhitwetsagul, Chaiyong, et al.
Published: (2024)
A Regression Testing Framework with Automated Assertion Generation for Machine Learning Notebooks
by: Yao, Yingao Elaine, et al.
Published: (2025)
by: Yao, Yingao Elaine, et al.
Published: (2025)
JunoBench: A Benchmark Dataset of Crashes in Python Machine Learning Jupyter Notebooks
by: Wang, Yiran, et al.
Published: (2025)
by: Wang, Yiran, et al.
Published: (2025)
Reconciling Complexity and Simplicity in the Business Model Canvas Design Through Metamodelling and Domain-Specific Modelling
by: Benkeltoum, Nordine
Published: (2026)
by: Benkeltoum, Nordine
Published: (2026)
The Machine Learning Canvas: Empirical Findings on Why Strategy Matters More Than AI Code Generation
by: Prause, Martin
Published: (2026)
by: Prause, Martin
Published: (2026)
Analysing Python Machine Learning Notebooks with Moose
by: Mignard, Marius, et al.
Published: (2025)
by: Mignard, Marius, et al.
Published: (2025)
A Flexible Cell Classification for ML Projects in Jupyter Notebooks
by: Perez, Miguel, et al.
Published: (2024)
by: Perez, Miguel, et al.
Published: (2024)
Improving Quantum Developer Experience with Kubernetes and Jupyter Notebooks
by: Kinanen, Otso, et al.
Published: (2024)
by: Kinanen, Otso, et al.
Published: (2024)
Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility
by: Jin, Bihui, et al.
Published: (2026)
by: Jin, Bihui, et al.
Published: (2026)
Containing the Reproducibility Gap: Automated Repository-Level Containerization for Scholarly Jupyter Notebooks
by: Samuel, Sheeba, et al.
Published: (2026)
by: Samuel, Sheeba, et al.
Published: (2026)
Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models
by: Jin, Bihui, et al.
Published: (2025)
by: Jin, Bihui, et al.
Published: (2025)
Bridging the Prototype-Production Gap: A Multi-Agent System for Notebooks Transformation
by: Elhashemy, Hanya, et al.
Published: (2025)
by: Elhashemy, Hanya, et al.
Published: (2025)
LEO: An Open-Source Platform for Linking OMERO with Lab Notebooks and Heterogeneous Metadata Sources
by: Guerrero, Rodrigo Escobar Díaz, et al.
Published: (2025)
by: Guerrero, Rodrigo Escobar Díaz, et al.
Published: (2025)
When Are Reactive Notebooks Not Reactive?
by: Zheng, Megan, et al.
Published: (2025)
by: Zheng, Megan, et al.
Published: (2025)
Evolving with AI: A Longitudinal Analysis of Developer Logs
by: Sergeyuk, Agnia, et al.
Published: (2026)
by: Sergeyuk, Agnia, et al.
Published: (2026)
A Systematic Literature Review of Software Engineering Research on Jupyter Notebook
by: Siddik, Md Saeed, et al.
Published: (2025)
by: Siddik, Md Saeed, et al.
Published: (2025)
Optimizing an IDE for an Evolving Language Ecosystem
by: Welc, Adam, et al.
Published: (2026)
by: Welc, Adam, et al.
Published: (2026)
Evolaris: A Roadmap to Self-Evolving Software Intelligence Management
by: Liu, Chengwei, et al.
Published: (2025)
by: Liu, Chengwei, et al.
Published: (2025)
Similar Items
-
Hidden Gems in the Rough: Computational Notebooks as an Uncharted Oasis for IDEs
by: Titov, Sergey, et al.
Published: (2024) -
Untangling Knots: Leveraging LLM for Error Resolution in Computational Notebooks
by: Grotov, Konstantin, et al.
Published: (2024) -
Observing Fine-Grained Changes in Jupyter Notebooks During Development Time
by: Titov, Sergey, et al.
Published: (2025) -
Themisto: Jupyter-Based Runtime Benchmark
by: Grotov, Konstantin, et al.
Published: (2025) -
Human to Document, AI to Code: Comparing GenAI for Notebook Competitions
by: Settewong, Tasha, et al.
Published: (2025)