time and space complexity analysis
Nobody has claimed this yet.
- Dominant language
- C
- Stars
- 19
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
measure and report the wallclock time, tokens used, etc.
Time complexity: O(I × (L + C + T)) where:
I = number of iterations (up to 6 in experiments)
L = LLM inference time (depends on context length)
C = compilation time
T = testing time
Space complexity:
Bounded by LLM context window (limiting code size)
Storage for multiple code versions and conversation history
Linear in the size of the codebase being optimized
Contributor guide
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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
Start by inspecting the driver that ties together the compiler and AI models, especially the experiment loop described in the issue. Identify where wallclock time, token usage, compilation, testing, code versions, and conversation history can be measured. Done means the requested measurements are reported and the stated time and space complexity are supported by the results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- c
- Domain
- compilers, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100