Define normalization rules
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- documentation, machine-learning
Research direction
Start with the raw conventional commit data and trace how normalized values feed the n-gram tables and neural model. Resolve the casing, whitespace, character, scope, proper-noun, and emoji questions, then document rules in a format that can be automated; done means every Success Criteria item is addressed.
Written by the indexing model from the issue text.
Description
Summary
Define rules for normalizing raw conventional commit data into a consistent format.
Success Criteria
- Casing rules defined (lowercase types, scopes, etc.)
- Whitespace handling documented
- Character normalization rules (unicode, special chars)
- Scope canonicalization rules (e.g., aliasing)
- Rules documented in a format that can be automated
Context
Raw commit messages vary wildly in formatting. Normalization ensures the n-gram tables and neural model see consistent patterns.
Open Questions
- Should we preserve original casing for proper nouns in scope?
- How to handle emoji in commit messages?
- Dominant language
- Python
- Stars
- 0
- Forks
- 0
- PR merge metrics
- No merged PRs in 30d
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.
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