Estimate the time complexity of an accepted run on request - #75
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An accepted run can be rerun on inputs of growing size from a per-problem generator. The runner measures each size's CPU time in one sandbox container, fits it to a power of n and names the class, and the room sees the result next to the problem's expected class. Analyses only run when no submission is waiting, within a time budget, one per person at a time and 20 an hour. Two Sum, Valid Parentheses, Best Time to Buy and Sell Stock and 3Sum support it to start.
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📝 WalkthroughWalkthroughThe change adds optional complexity analysis for accepted submissions. Problems provide input generators and expected complexity classes. A queued runner measures program growth and stores results, which the room interface can display. ChangesSubmission Complexity Analysis
Priority: ⬇️ Low Estimated code review effort: 4 (Complex) | ~45 minutes Change: Feature Sequence Diagram(s)sequenceDiagram
participant RoomView
participant ComplexityPanel
participant SubmissionAPI
participant SubmissionRoute
participant SubmissionService
participant SubmissionDAO
participant Runner
participant RoomSocket
RoomView->>ComplexityPanel: Render for eligible accepted submission
ComplexityPanel->>SubmissionAPI: Request analysis
SubmissionAPI->>SubmissionRoute: POST /submissions/{submission_id}/analysis
SubmissionRoute->>SubmissionService: Validate request
SubmissionService->>SubmissionDAO: Queue eligible analysis
SubmissionDAO-->>SubmissionService: Pending submission
SubmissionService-->>SubmissionRoute: Submission response
SubmissionRoute->>RoomSocket: Broadcast pending submission
Runner->>SubmissionDAO: Claim and complete analysis
SubmissionDAO->>RoomSocket: Notify submission_judged
RoomSocket-->>ComplexityPanel: Deliver updated submission
Merge Risk: 🔵 Low · up to Repeated failed-analysis requests can bypass the hourly limit and consume runner time. The change is mergeable with explicit acceptance of that bounded risk or a request-counting fix. Security Architecture ReviewSecurity architecture risk: 🟡 Moderate · up to A room member can repeatedly request analysis of a failed run without using another unit of the intended hourly allowance, allowing repeated competition for the shared runner. One-analysis-at-a-time and sandbox controls limit each attempt, but the request limit does not hold across retries. Retained concerns
Security review detailsSecurity Blast Radius
Security Findings and Attack Paths
Trust Boundaries and Controls
Resilience and Maintainability Implications
Hardening Proposals
🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
Full details: Docstring CoverageExplanation Docstring coverage is 15.69% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 51 functions across 17 files. (4 skipped: 4 unsupported.) ✨ Finishing Touches 💡 1📝 Generate docstrings 💡
🧪 Generate unit tests (beta)
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Actionable comments posted: 1
- 🪄 Fix CodeRabbit comments on this PR
🤖 Prompt to fix review comments
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only still-valid issues, skip the rest with a brief reason, keep changes
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Inline comments:
In `@apps/backend/app/dao/submissions.py`:
- Around line 125-145: Update count_analyses_since to count request records by
user and time, and update request_analysis to insert a separate analysis-request
record for each successful status update in the same transaction. Preserve the
existing behavior when the update matches no submission, and ensure retries
retain the original requester’s count.
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CONTRIBUTING.mdapps/backend/app/dao/problems.pyapps/backend/app/dao/submissions.pyapps/backend/app/routes/submissions.pyapps/backend/app/runner/__main__.pyapps/backend/app/runner/complexity.pyapps/backend/app/runner/sandbox.pyapps/backend/app/schemas/problems.pyapps/backend/app/schemas/submissions.pyapps/backend/app/services/submissions.pyapps/backend/migrations/V13__complexity_analysis.sqlapps/backend/tests/conftest.pyapps/backend/tests/test_analysis.pyapps/backend/tests/test_complexity.pyapps/backend/tests/test_sandbox.pyapps/web/src/components/ComplexityPanel.tsxapps/web/src/hooks/UseWebSocket.tsapps/web/src/lib/api.tsapps/web/src/routes/rooms/RoomView.tsxdocs/architecture.mddocs/judge-and-sandbox.md
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What and why
After an accepted verdict, anyone in the room can press Analyze complexity. The runner reruns the solution on inputs of growing size and estimates how its running time grows. The room then sees the measured class next to the problem's expected class, with a small chart of time against n.
How it measures (
app/runner/complexity.py):x in some_listoritertools.combinationsas one step and would call a quadratic or cubic brute force linear.Load and safety:
BUDGET_SECONDS= 6 of runner time per analysis, andPER_RUN_SECONDS= 2.5 per size. A solution that outgrows them is stopped, and the note says at which n.ANALYSES_PER_HOUR= 20. A second press by the partner returns the analysis already queued.Problems opt in by setting
complexity_generatorandexpected_complexity, as described in CONTRIBUTING. V13 adds them for Two Sum, Valid Parentheses, Best Time to Buy and Sell Stock (linear) and 3Sum (quadratic). Every other problem shows no button.Deploying
V13 is a migration, so deploy the API first (
./infra/deploy.sh, which backs up first), then merge so Vercel ships the web app.Not verified: whether gVisor (
runsc) reports child-process CPU time. If it doesn't, the code falls back to wall time, which is noisier. Check one analysis on the server after deploying.How this was verified
make test: 140 passed, 6 skipped. The skipped tests need Docker inside the test container. New tests cover:analyze_in_container) was run by hand: Two Sum was linear in 1.8 s wall, 3Sum quadratic in 3.7 s. A test for it is added totest_sandbox.pyfor machines with Docker.inon a slice 2.11 (the line-count failure case)itertools.combinations2.83Summary by CodeRabbit