Fuzz testing
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- distributed-systems, testing
Research direction
Start by locating the existing distarray test modules and the test harness for launching IPython engines. Review how random inputs, distributed dimensions, ufuncs, and reductions are currently tested. Done means a separate fuzz-testing module covers the requested engine counts, array sizes, distribution mixes, fundamental operations, and listed edge cases.
Written by the indexing model from the issue text.
Description
For robustness, it would be good to have a separate test module that:
- is run with a random number of IPython engines (between 1 and 20 or so, inclusive)
- creates random distarrays with random sizes in each dimension (between 0 and 1e6, inclusive)
- with a random mix of undistributed, block distributed, and block cyclic distributed dimensions
- that tests ufuncs, reductions, and other fundamental stuff
We could test the edge cases in a separate test class as well -- size of zero in one or more dimensions, all dimensions undistributed, using a view with just one target /engine, etc.
- Dominant language
- Python
- Stars
- 5
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
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.
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