dc-legacy-alloc-planning-season

Public task · AllocBench

← AllocBench

Reproduce a full planning season: four re-run cycles as lots land and locks accumulate.

Version
Category
software-engineering
Difficulty
expert
Model configurations
3
Attempts
13
Public trials
134 passed
Median runtime
16m 7s

Instruction

# Replay a planning season

The old planning module was retired last quarter and its allocation engine's source did not survive the migration. Its captured production runs are in `audit/` — request/plan pairs, exactly as the engine consumed and produced them. The decision policy was never written down; the archive is the only spec.

The engine never ran once; it ran all season. After the opening cycle in `data/scenario.json`, lots keep landing and reviewed phases keep locking — each cycle's plan becomes the next cycle's commitments. The verifier replays four such cycles against your engine, so a small policy error early compounds into every later cycle.

Implement the engine at `allocator/solve.py` (entry point in
`allocator/README.md`) so it reproduces the legacy engine's planning
behavior on any request, and use it to plan `data/scenario.json`. The engine
re-runs as the world changes — new lots land and phases lock between runs —
and grading is outcome equivalence with the legacy engine, not matching its
exact lot choices.

Check plan structure with
`python3 contracts/validate.py <request.json> <response.json>`.

Public trials

gemini-3.1-pro-preview0 of 1 passed

GPT 5.6 Sol1 of 1 passed

Results by model

Model · harnessMean rewardRange± SEAttempts
GPT 5.6 SolOpenCode100.0%100% – 100%—1
Muse Spark 1.3 ContributorOpenCode55.8%0% – 100%12.5 pp11
gemini-3.1-pro-previewOpenCode51.0%51% – 51%—1