paritytech / paritytech/revive
Explore fuzzing and coverage improvements with LLMs
Nobody has claimed this yet.
- Dominant language
- Rust
- Stars
- 102
- Forks
- 26
- Avg merge
- 1d 13h
- Merged PRs (30d)
- 6
Description
After #529 lands, we can build LLVM with coverage instrumentation.
I'd like to increase code coverage (and fuzzing) of the retester suite.
A novel approach would be to let LLMs loop with the goal to find Solidity or Yul fixtures and compiler settings that increase code coverage. My intuition is that LLMs should be pretty good with this. Should start with cheap and fast small parameter local models to pick the low hanging fruits. They can just look at coverage reports and start with some Solidity fixtures, and reason about how to reach uncovered code paths.
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.
Research direction
After #529 lands, inspect how the retester suite is built with coverage instrumentation and how its coverage reports are produced. Explore small local models generating Solidity or Yul fixtures and compiler settings, then measure whether the suite reaches previously uncovered paths. Done means fuzzing and code coverage improve with a reproducible approach.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- rust, solidity
- Domain
- ai, compilers, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100