CR141 verifies the account-level consequences of DeFi governance parameter changes before execution and has been validated on 28 historical Compound governance proposals with 474 predicted and 474 observed account state transitions.
DeFi governance publishes parameter changes as numbers. A proposal reads
collateral factor 0.75 → 0.80 and that is the whole visible consequence. The
questions governance participants actually need answered — which accounts become constrained,
how many positions change state, which market drives the outcome — are not part of the
proposal record. Decisions are therefore taken on parameters, not on consequences.
CR141 converts an executed governance proposal into a measurable population and a set of
account state transitions. For each proposal it reads the protocol state at block
b − 1 — the block immediately before execution — recomputes each account's
collateral buffer with the old and the new collateral factor, and reports every account whose
buffer crosses zero.
This is governance impact verification rather than governance forecasting. The input is a change that already executed, and the block used for the computation is strictly the block before execution. Post-execution data is used only afterwards, as the answer key.
b − 1, in fixed-point wei
arithmetic, integer only, no sampling and no Monte Carlo.| Measure | Result |
|---|---|
| Governance proposals replayed | 28 |
| Collateral factor changes | 141 |
| Analyzed accounts | 89,645 |
| Predicted account state transitions | 474 |
| Observed account state transitions | 474 |
| Difference | 0 |
| Proposals with exact set equality | 28/28 |
| Proposals producing a non-empty transition set | 14/28 |
| Transitions attributable to more than one market | 92 |
Audit status: CLOSED. Build cr141-v1.3.2-openapi at commit 412d627.
These terms are used with one meaning across the dashboard, the API and the documentation:
CR141 performs governance impact analysis: for a DeFi governance proposal that changes collateral factors, it recomputes every affected account's collateral buffer at the block before execution, and reports which accounts cross a critical threshold, how many change state, and which market drives each change.
By exact replay of executed Compound governance history. For each of 28 proposals the predicted set of account state transitions was compared with the set observed on-chain after execution. The falsification criterion was exact set equality, not an error tolerance. 474 predicted transitions and 474 observed transitions matched, with zero differences, on 89,645 analyzed accounts.
It is the estimate, made before a governance vote executes, of which accounts a parameter change actually affects and how. A collateral factor change is published as one number; governance impact analysis converts that number into a population, a set of state transitions and a market attribution.
A collateral factor sets how much of a supplied asset counts toward borrowing capacity in a lending market. Raising or lowering it changes every borrower's collateral buffer at once. CR141 treats each such change as a measurable event: one market, one before value, one after value, one execution block.
28 executed Compound governance proposals, carrying 141 collateral factor changes, covering 89,645 analyzed accounts and 474 predicted state transitions.
Yes, as counterfactual governance analysis over frozen contributions. Given a proposal and an alternative collateral factor, CR141 reports the affected population and the newly flipped and healed accounts without touching the chain. What CR141 does not do is forecast prices or future protocol behaviour: the simulation holds the observed block state fixed.
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