How to Use Forking to Experiment with New Governance Models

Governance forking is the process of creating a functional copy of a decentralized autonomous organization's (DAO) core components—its smart contracts, treasury, and token distribution—to experiment with new rules. Unlike a simple code fork, a governance fork replicates the live state, allowing token holders to migrate and participate in a parallel governance system. This method is used to stress-test proposals that are too radical or risky to implement on the main protocol, such as changing quorum requirements, introducing quadratic voting, or altering fee distribution mechanisms without jeopardizing the original DAO's stability.

The technical process begins with forking the canonical governance contracts from a source like the Compound Governor Bravo repository. You must also snapshot the token holder ledger at a specific block number to establish initial voting power. Tools like Hardhat or Foundry are essential for deploying the forked contracts to a testnet or a mainnet fork. A critical step is ensuring the forked treasury is seeded, often by a multi-sig of forking proponents, to enable real economic experiments around fund allocation and grants.

Practical experiments often focus on mechanism design. For example, you could implement vote delegation with multipliers for long-term holders, or a rage-quit function that allows dissenting members to withdraw a proportional share of the treasury. Another common test is moving from a pure token-weighted vote to a hybrid model incorporating non-transferable "reputation" points for contributors. These changes are proposed and voted on using the new forked system itself, creating a live feedback loop on governance efficacy.

Successful governance forks require clear exit strategies and evaluation metrics. Participants should define success criteria upfront: is the goal increased voter turnout, more efficient proposal processing, or fairer resource distribution? After the trial period, the fork can be dissolved, with lessons distilled into a formal proposal for the original DAO. This approach transforms governance debates from theoretical discussions into data-driven decisions, providing concrete evidence for or against a proposed change based on its actual performance in a controlled, sovereign environment.

Forking a governance system involves creating a complete, isolated copy of a DAO's smart contracts and state on a local or test network. This is the primary method for developers and researchers to test new governance proposals, modify voting logic, or simulate treasury actions without risking real funds or affecting the main protocol. You'll need a basic understanding of smart contracts, Ethereum tooling like Hardhat or Foundry, and access to the DAO's verified contract addresses on a block explorer like Etherscan. The core contracts to fork typically include the governance token, the governor contract (e.g., OpenZeppelin's Governor), and the treasury (e.g., a TimelockController).

To begin, set up a local development environment. Using Hardhat, you can configure a forked network in your hardhat.config.js file. Specify the JSON-RPC URL of a provider like Alchemy or Infura and the block number you wish to fork from. Forking from a recent block ensures you have the most up-to-date contract state, including token balances and proposal data. With Foundry, you can start a forked instance directly from the command line using anvil --fork-url $RPC_URL. This creates a local Anvil instance that mirrors the mainnet state, allowing you to interact with contracts as if you were on the live network.

Once your local fork is running, you need to impersonate accounts to simulate governance actions. Since you control the forked network, you can assign yourself the voting power of any address. In Hardhat, use await hre.network.provider.request({ method: 'hardhat_impersonateAccount', params: [address] }) and then send transactions from that address. In Foundry's cast or via a script, use the --unlocked flag with the --from address. This allows you to act as a large token holder to create proposals, vote, or execute transactions from the DAO treasury, testing the entire governance lifecycle from proposal to execution in a controlled sandbox.

The most powerful aspect of forking is the ability to deploy and test modified governance logic. After forking the live contracts, you can write and deploy your own upgraded versions—for example, a new governor contract with a different voting delay or quorum threshold. You can test these changes by creating proposals, simulating voter behavior, and executing them against the forked treasury. This process is essential for security auditing and mechanism design before proposing changes to the live DAO. Always test edge cases, such as failed proposals, malicious proposals, and emergency execution scenarios.

For realistic experimentation, populate your forked environment with historical data. Import past proposal IDs and their states to understand how your modifications would have altered historical outcomes. Use tools like Tenderly or OpenZeppelin Defender to simulate complex multi-step proposals and their effects on the treasury. Document your testing methodology and results clearly, as this forms the basis for a credible governance improvement proposal (GIP) to the community. A well-tested fork demonstration can significantly increase the likelihood of your proposed model being adopted by the mainnet DAO.

Forking a smart contract state is the process of creating a complete, local copy of a live blockchain's data at a specific block. This includes the code, storage, and balances of the target protocol. Tools like Hardhat Network, Ganache, or Anvil enable this by allowing you to fork from a public RPC endpoint (e.g., https://eth-mainnet.g.alchemy.com/v2/your-key). The forked environment behaves exactly like the mainnet, but all transactions are executed locally and have no real-world consequences. This is the foundational step for testing governance changes without risking protocol funds or requiring a testnet deployment.

To begin, you need the target contract's address and the block number you wish to fork from. The block number is critical for reproducibility; it ensures your fork uses a consistent, historical state. In your development environment, configure the network fork. For example, in a Hardhat configuration file (hardhat.config.js), you would add a network definition:

javascriptCopy
module.exports = {
  networks: {
    hardhat: {
      forking: {
        url: "ALCHEMY_MAINNET_URL",
        blockNumber: 16890420
      }
    }
  }
};

When you start your local node with npx hardhat node, it will silently fetch and cache the required state.

Once your local fork is running, you can interact with the protocol's contracts as if you were on mainnet. Use the Hardhat Console or write test scripts to impersonate accounts, including governance token holders or the protocol's timelock controller. For instance, you can use await hre.ethers.provider.send('hardhat_impersonateAccount', [address]) to gain control of a specific address and propose a new governance vote. This allows you to simulate the entire proposal lifecycle—submission, voting, queuing, and execution—against the real contract logic and state.

This method is superior to deploying mock contracts because it preserves the complex, interconnected state of the actual protocol. You can test interactions with price oracles, liquidity pools, and collateral factors that would be difficult to replicate manually. It also lets you experiment with extreme scenarios, like testing a governance proposal's effect when the total value locked (TVL) is at an all-time high or when certain market conditions are met, by forking from a block that captured that specific moment in time.

After forking, you can modify parameters to test new models. Want to see how a proposal fares with a 48-hour voting delay instead of 72 hours? You can deploy a slightly modified version of the governance contract, point it to the forked state of the other protocol contracts, and run your simulation. This step isolates the variable you're testing—the governance mechanism—while holding all other system dependencies constant. It's the most accurate way to predict the outcomes and unintended side effects of a governance change before proposing it on-chain.

With your forked network running, you can now deploy the experimental governance module. This involves writing and compiling the smart contract code. For a basic quadratic voting contract, you might use a Solidity structure that tracks voter weight as the square root of their token balance. Use a development framework like Hardhat or Foundry to compile the contract, ensuring it targets the correct EVM version (e.g., london) compatible with your forked chain. The key is that you are deploying this contract to your local forked environment, not a live network.

Deployment is done via a script that uses an unlocked account from your forked chain. For example, using Hardhat and Ethers.js, you would connect to the local node (http://localhost:8545), get the signer for a pre-funded account (like 0xf39Fd6e51aad88F6F4ce6aB8827279cffFb92266), and deploy the contract. The transaction will be mined instantly. Record the deployed contract address, as this is your new "governance" system for the experiment. You can verify the deployment by checking the contract code at that address using the node's RPC methods.

Next, you need to integrate this module with the existing forked protocol. This often means updating the protocol's governance address pointer. If the original protocol has a governor contract, you could write a proposal script that calls _setGovernance(address newGov) on the main protocol contract, directing it to your new module. Execute this script from a privileged account to simulate a successful governance proposal. This step "wires" your experimental module into the system, allowing you to test how the protocol behaves under the new rules.

Now, simulate governance actions. Write test scripts to execute the core functions of your module. For a quadratic voting test, script a series of votes from different addresses with varying token balances. Calculate the expected voting power (e.g., sqrt(balance)) and assert that the contract's tally matches. Use console.log statements or a test runner's reporting to track outcomes. This is where forking is invaluable: you can use real token balances from the forked state without spending real funds, testing the module's logic against authentic data.

Finally, analyze the results and iterate. Examine the transaction logs and final state changes. Did the vote pass as expected? Were there unexpected gas costs or revert errors? Based on the findings, you can modify your contract code and redeploy in a new test cycle. This rapid iteration loop—fork, deploy, test, analyze—is the core advantage of using a fork for governance R&D. It allows for rigorous, low-risk experimentation before considering any live deployment or formal audit.

Effective governance experiments require clear, measurable goals. Before deploying your forked DAO or protocol, define the Key Performance Indicators (KPIs) you want to test. These could include voter participation rates, proposal throughput, average delegation depth, or treasury allocation efficiency. For example, if you're testing a new quadratic voting module, your primary KPI might be the distribution of voting power post-implementation compared to the original one-token-one-vote model. Document these target metrics in your experiment's design document.

To capture these metrics, you must instrument your forked smart contracts and frontend. This involves emitting custom events for on-chain actions and logging off-chain user interactions. For a governance contract, you would add events like VoteCast(address voter, uint256 proposalId, uint256 weight, string support). Use a blockchain indexer like The Graph to create a subgraph that queries these events, or employ a node RPC provider with enhanced APIs to log transaction data. This setup creates a verifiable, on-chain audit trail for all governance actions.

Off-chain metrics are equally important and often require dedicated tooling. To measure community sentiment and discussion quality, you can integrate with forum platforms like Discourse or Commonwealth via their APIs. Tools like SourceCred can help quantify contribution value. For a holistic view, consider using a dashboard framework like Dune Analytics or Flipside Crypto to create a public dashboard that aggregates both on-chain and off-chain data, providing real-time visibility into your governance experiment's performance for all participants.

The primary goal of a governance fork is to test new models in a real, but contained, economic environment. After your fork has been live and operational—handling real transactions, voter participation, and treasury management—you must systematically evaluate its performance. Define clear Key Performance Indicators (KPIs) upfront, such as voter turnout, proposal execution time, treasury allocation efficiency, or resilience to governance attacks. Compare these metrics against the original chain's baseline. Tools like Tally or Boardroom can provide analytics, but you may need to build custom dashboards using subgraph queries to track fork-specific data.

Documentation is critical for any potential re-merge. Maintain a detailed changelog of all governance contract modifications, including the Governor contract address, voting logic adjustments, and any new module integrations (e.g., OpenZeppelin Governor extensions). For example, if you implemented a quadratic voting mechanism, document the contract function (_countVote) overrides and the library used. This technical log should be paired with a narrative report analyzing what worked, what failed, and why. This becomes the formal proposal for upstream changes.

The re-merging strategy depends on the parent protocol's own governance. If the mainnet protocol is upgradeable via a DAO vote, your fork's successful innovations can be packaged as an executable proposal. This often involves creating a formal Ethereum Improvement Proposal (EIP) style document or a Governance Proposal that references your fork's on-chain history and audit reports. If the parent protocol is immutable, re-merging may mean advocating for the changes in a future hard fork or inspiring a new protocol iteration. The code and lessons become public goods for the ecosystem.

Consider the social and political dimensions. A successful fork can create a community with different values. Re-integrating may require building consensus not just on-chain, but in forums and social channels. Present your findings transparently, highlighting benefits for all stakeholders. Use the fork's treasury to fund a security audit of the proposed changes—this is a non-negotiable step for gaining mainnet trust. The final output of this phase is a concrete, audited, and community-vetted upgrade path that translates experimental on-chain governance into production-ready innovation.

By forking a network like Ethereum or a specific DAO's smart contracts, you create a controlled environment to model and test governance changes. This allows you to validate assumptions about voter behavior, incentive alignment, and security without risking real assets or disrupting a live community. Tools like Hardhat, Foundry, and Ganache make it straightforward to spin up a local fork, while services like Alchemy and Infura can provide archival node access for more complex simulations.

Your next step is to design a specific experiment. Consider testing mechanisms like: quadratic voting to reduce whale dominance, conviction voting for long-term alignment, futarchy for prediction market-based decision-making, or multisig with time-locks for enhanced security. Use the forked environment to deploy modified versions of governance contracts such as OpenZeppelin Governor or Compound's Governor Bravo. Simulate proposal submission, voting, and execution to identify edge cases and attack vectors.

After running your simulation, analyze the data. Use block explorers on your fork to track transaction flows and voter participation. Tools like Tenderly can help debug and visualize contract interactions. The goal is to gather concrete evidence on the mechanism's efficacy, gas costs, and potential vulnerabilities. This data is crucial for building a compelling case to present to the actual DAO community, moving your experiment from a theoretical fork to a formal governance proposal.