tensorflow / tensorflow/probability
Try out NBTest: A smarter tool for testing jupyter notebooks
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- Dominant language
- Jupyter Notebook
- Stars
- 4.4k
- Forks
- 1.1k
- PR merge metrics
- No merged PRs in 30d
Description
Hi probability developers,
We’re researchers at Cornell University focused on software quality assurance (our group). We’d love to introduce you to NBTest, a new tool we’ve built to make regression testing easier and more effective in Jupyter Notebooks.
NBTest automatically detects important program metrics and generates statistically sound assertions. This helps catch subtle regressions and inconsistencies that traditional tools may miss.
Getting started is simple—you can follow our installation and usage instructions and start integrating it into your notebooks in minutes.
We’d be excited if you gave it a try, and we’d love to hear your thoughts. If you're interested, we’d also be happy to set up a quick chat to talk more!
Best regards,
Elaine
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No repository file, test, or entry point is identified. Start with the linked NBTest installation and usage instructions if evaluating the proposal, then determine whether the maintainers want an integration or other concrete change; the issue does not define a completion condition.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100