How to Structure Complex EVM Calls

The Ethereum Virtual Machine (EVM) executes transactions as a sequence of low-level opcodes. A simple token transfer involves a single CALL opcode. However, modern DeFi protocols and smart contract systems require orchestrating multiple calls within a single transaction. These complex patterns enable powerful functionalities like flash loans, multi-hop swaps, and gas-efficient batch operations. Understanding how to structure these calls is essential for building advanced dApps and interacting with protocols like Uniswap V3, Aave, and Compound.

The core building blocks are the call, delegatecall, and staticcall opcodes, accessible in Solidity via low-level functions. A standard call forwards value and executes code in the context of the target contract. Delegatecall is critical for upgradeable proxies and library patterns; it executes code from the target contract but uses the storage of the calling contract. Staticcall, introduced in the Byzantium hard fork, is used for view functions and guarantees no state modification, which is vital for safe off-chain simulations and MEV protection strategies.

To execute a complex call pattern, you often use a router or multicall contract. For example, a user might want to swap ETH for DAI on Uniswap and then deposit that DAI into Aave in one transaction. This is structured as a series of delegatecalls to a helper contract or a single contract that makes external calls sequentially. The key challenge is managing state changes, gas limits, and error handling across each step to ensure atomic execution—where the entire transaction reverts if any single call fails.

Here is a simplified Solidity example of a batch operation using a helper function:

solidityCopy
function executeCalls(address[] calldata targets, bytes[] calldata data) external payable {
    for (uint i = 0; i < targets.length; i++) {
        (bool success, ) = targets[i].call(data[i]);
        require(success, "Call failed");
    }
}

This pattern is used by protocols like Uniswap's Multicall2 and MakerDAO's DSSProxy. It allows bundling approval, swap, and deposit logic, saving the user gas and reducing the risk of partial execution.

Security is paramount when crafting complex calls. Re-entrancy guards must be considered, especially when calls interact with untrusted contracts. Using staticcall for read-only operations and carefully validating data returned from delegatecall prevents state corruption. Tools like Ethereum's Tracer and Tenderly are indispensable for simulating these transaction flows and inspecting intermediate state changes before broadcasting to mainnet.

Mastering these patterns unlocks the ability to build sophisticated on-chain automations, optimize gas costs through batching, and create seamless user experiences in DeFi. The next step is exploring specific implementations like flash loan arbitrage bots, cross-chain messaging layers, and account abstraction wallets that rely heavily on these advanced EVM call structures.

An EVM call is a request to execute code at a specific contract address. While simple calls transfer value or invoke a single function, complex calls orchestrate multiple operations—like swaps, approvals, and deposits—within a single atomic transaction. This is essential for DeFi interactions, where a user's intent (e.g., "provide liquidity") often requires a sequence of steps. Structuring these calls correctly prevents failed transactions, saves gas, and ensures the entire operation succeeds or reverts as one unit, protecting users from partial execution states.

The core tool for building these calls is ABI Encoding. The Application Binary Interface defines how to encode function calls and data for the EVM. Use the abi.encode, abi.encodePacked, or abi.encodeWithSignature methods in Solidity, or their equivalents in libraries like ethers.js (interface.encodeFunctionData). For a call to a function like swapExactTokensForETH, you must encode the exact function selector and all its parameters (amounts, paths, deadlines) into the data field of the transaction. Mis-encoded data is the most common cause of call failure.

To execute a sequence, you often use a proxy contract or multicall. Instead of making separate transactions, you bundle calls. A common pattern is a router contract (like Uniswap's) that internally calls multiple pools. For custom sequences, you can deploy a helper contract that uses delegatecall or call in a loop. Off-chain, you can use the multicall3 contract (0xcA11bde05977b3631167028862bE2a173976CA11) to aggregate multiple static or state-changing calls into one, reducing RPC round trips and ensuring consistent state reads.

Always consider gas estimation and safety. Complex calls consume more gas. Use eth_estimateGas RPC method to simulate the transaction before broadcasting. Implement checks like deadline parameters and slippage tolerance directly in your call data to protect against front-running and price changes. For calls involving token transfers, remember that the calling contract must handle approval—either via a prior transaction or within the call sequence using approve followed by the action, though this requires careful attention to reentrancy and security patterns.

Testing is critical. Use forked mainnet environments in Foundry or Hardhat to simulate your complex call against real contract states. Tools like Tenderly or OpenZeppelin Defender can simulate and debug transactions, visualizing the call trace and state changes. Start by building and testing individual calls, then combine them, verifying after each step that intermediate token balances and allowances are as expected. This methodical approach ensures your structured EVM call performs reliably when deployed.

Structuring complex EVM calls involves bundling multiple operations into a single atomic transaction. This is essential for DeFi interactions like swapping tokens and providing liquidity in one step, or for NFT operations such as minting and listing. The primary benefit is atomicity: either all operations succeed, or the entire transaction reverts, preventing partial execution states. This is typically achieved using a proxy contract or multicall pattern, where a single entry point delegates logic to other functions or contracts.

The most common pattern is the multicall, popularized by Uniswap V3's Multicall.sol. It allows you to aggregate multiple function calls (abi.encodeWithSelector) into a single bytes[] array and execute them sequentially within the same transaction context. This preserves msg.sender and block.number across calls, which is crucial for consistent access control and logic. For more complex, conditional logic, developers implement a dispatcher or router contract that contains the business logic to orchestrate calls to external protocols based on input parameters.

When designing these structures, gas optimization and security are paramount. Batching calls saves on base transaction costs (21,000 gas) but can increase total gas if calls are inefficient. Use staticcall for view functions and be mindful of reentrancy risks when calls interact with untrusted contracts. Always validate and sanitize all user inputs and external call return data using abi.decode. Tools like Tenderly or OpenZeppelin Defender can simulate these complex transactions to estimate gas and debug reverts before mainnet deployment.

A practical example is a leveraged yield farming transaction: 1) Flash loan DAI from Aave, 2) Swap DAI for ETH/DAI LP tokens on Uniswap, 3) Deposit LP tokens into a farming contract like Curve, and 4) Repay the flash loan—all in one call. This requires precise structuring to ensure the flash loan callback correctly triggers the subsequent steps and that the final contract holds enough funds for repayment. Failure at any point must cause a full revert.

For developers, libraries like OpenZeppelin's Address utility (for safe calls) and Solidity's try/catch blocks (for handling selective failures) are indispensable. The emerging ERC-4337 Account Abstraction standard further revolutionizes this by allowing user operations (UserOperation) to bundle multiple calls with sponsored gas and custom signature schemes. Mastering these patterns is key to building advanced, gas-efficient, and user-friendly decentralized applications.

A multicall contract is a smart contract that aggregates multiple function calls into a single transaction. This pattern is essential for dApps that need to execute several read or write operations atomically. By batching calls, you reduce the overhead of multiple transaction confirmations, lower gas costs for users, and prevent state inconsistencies that can occur if a series of individual transactions fails partway through. Popular implementations include the MakerDAO Multicall and Uniswap's Multicall2, which have become standard utilities in the EVM ecosystem.

The core function of a multicall contract is straightforward: it takes an array of Call data structures, each containing a target address and calldata payload, and executes them sequentially. A basic Solidity interface looks like this:

solidityCopy
function multicall(Call[] calldata calls) external returns (bytes[] memory results) {
    results = new bytes[](calls.length);
    for (uint256 i = 0; i < calls.length; i++) {
        (bool success, bytes memory result) = calls[i].target.call(calls[i].data);
        require(success, "Multicall call failed");
        results[i] = result;
    }
}

This loop uses the low-level call function, which forwards the provided calldata to each target contract. The require statement ensures the entire batch reverts if any single call fails, guaranteeing atomicity.

For more robust applications, consider implementing a try/catch pattern within the multicall. Uniswap's Multicall2 introduces aggregate and blockAndAggregate functions that return a Result struct containing a success boolean and the return data. This allows partial failures where some calls can succeed while others fail, giving the calling contract flexibility to handle errors programmatically without reverting the entire batch. This is particularly useful for complex DeFi interactions where you might query multiple liquidity pools and want to proceed with the successful results.

When structuring complex calls, carefully manage state dependencies and gas limits. Calls execute in the order provided and share the same msg.sender and msg.value context, but each has its own gas stipend. If a later call depends on the state change from an earlier call in the batch, this will work correctly for write operations. However, be mindful of the block gas limit; batching too many heavy calls can cause the transaction to run out of gas. It's often practical to batch read-only staticcall operations separately from state-changing transactions.

To implement this in a frontend application using ethers.js v6 or viem, you encode your individual contract calls and pass them to the multicall contract. For example, using viem's multicall action with a public client is the simplest method for read operations. For writes, you would construct the calldata array manually. This pattern is ubiquitous in DeFi frontends for fetching balances, prices, and pool data in a single RPC request, dramatically improving load times and reducing the load on node providers.

The delegatecall opcode is a cornerstone of upgradeable smart contract design. Unlike a standard call, which executes code in the context of the target contract, delegatecall executes code from a target contract within the storage and msg.sender context of the caller. This means the logic contract's code runs as if it were part of the proxy contract, allowing the proxy's storage to be modified. This pattern separates contract logic from storage, enabling logic upgrades without migrating state. However, it introduces critical risks if storage layouts between proxy and logic contracts become misaligned.

A standard upgradeable proxy setup involves three key contracts: a Proxy, a Logic Implementation, and a ProxyAdmin. The proxy holds all state variables and uses delegatecall to forward transactions to the current logic implementation. The ProxyAdmin contract, typically controlled by a multi-sig, manages upgrade authorization. When a user calls the proxy, the fallback function uses delegatecall to execute the function in the logic contract. Popular standards like EIP-1967 define specific storage slots for the logic address and admin to prevent storage collisions. OpenZeppelin's implementations are the industry standard for this pattern.

Structuring complex calls requires careful attention to variable layout. Because delegatecall uses the proxy's storage, the order and types of state variables in the logic contract must exactly match the proxy's storage layout. Adding, removing, or reordering variables in a new logic contract will corrupt storage. To safely append new variables, they must be added after all existing ones in the inheritance chain. Tools like slither and hardhat-storage-layout can verify compatibility. Always use transparent or UUPS (EIP-1822) proxy patterns from audited libraries rather than custom implementations to mitigate delegatecall risks.

Beyond upgrades, delegatecall enables gas-efficient libraries and modular logic. Libraries like those in OpenZeppelin's utils can be deployed once and delegatecalled into by many contracts, saving deployment gas. However, any library using delegatecall must be stateless or use storage patterns that are compatible with all callers. A common mistake is assuming msg.sender in a delegatecall refers to the original EOA; it actually refers to the calling contract (the proxy). This affects access control and must be accounted for in the logic contract's design, often by reading an _admin or _owner variable from the proxy's storage.

Complex EVM calls often involve multiple state changes, external contract interactions, and data manipulations. The primary goal of structuring these calls is to minimize the number of SSTORE and SLOAD operations, as these are among the most expensive EVM opcodes. A key technique is to batch related state updates into a single transaction. For example, instead of calling separate functions to approve a token and then transfer it, design a single function that performs both actions, reducing the overhead of multiple transaction contexts and repeated storage access patterns.

Another fundamental strategy is to optimize data packing and memory usage. The EVM operates on 256-bit (32-byte) words. Storing multiple smaller variables (like uint64) in a single storage slot via bit packing can drastically cut costs. For instance, you can pack four uint64 values into one uint256 slot. Furthermore, prefer using calldata for function arguments over memory for arrays and structs when the data is only read, as calldata is a non-modifiable, gas-cheap data location. Use memory arrays only when you need to modify the data within the function's execution.

When making external calls, structure your logic to handle failures and refunds efficiently to avoid wasting gas. Use low-level calls (call, delegatecall, staticcall) for maximum control and gas savings compared to higher-level abstractions, but always implement checks for the success boolean and returned data. A common pattern is to cache external call results and state variables in local memory variables to avoid repeated, expensive external or storage lookups within a single transaction. For example, cache the balance of a user in a memory variable if you need to reference it multiple times in your function logic.

For complex, multi-step operations, consider using internal functions to reuse logic without the overhead of an external call. However, be wary of deep recursion and high stack usage. Structuring conditional logic to fail early (using require statements at the beginning) prevents the execution of subsequent, gas-intensive operations that would be rolled back. Tools like the Remix debugger, Hardhat Gas Reporter, and EthGasReporter are essential for profiling and identifying the most expensive lines of code in your call structures.

Finally, review and optimize the order of operations. Placing gas-intensive actions after all pre-conditions are verified and potentially refundable operations at the end of a function (following the Checks-Effects-Interactions pattern) can prevent gas loss in revert scenarios. For batch operations, using loops efficiently is crucial; avoid writing to storage inside loops if possible, and calculate aggregated results in memory before a single final storage write. Adopting these structural principles leads to more efficient and cost-effective smart contracts.

Structuring complex EVM calls effectively requires a systematic approach. You should now understand how to batch transactions using multicall contracts, manage state dependencies to avoid reverts, and implement gas optimization strategies like precomputing addresses and using low-level delegatecall. The primary goal is to create atomic, predictable, and cost-effective interactions with the blockchain, minimizing user friction and maximizing protocol reliability.

To solidify these concepts, practice by building a small project. For example, create a contract that performs a multi-step DeFi operation: 1) check a user's ERC-20 balance, 2) approve a router, and 3) execute a swap on Uniswap V3—all within a single transaction using a helper contract. Use Foundry's forge test to simulate the entire flow and measure gas costs. Refer to the OpenZeppelin Multicall implementation as a reference for batching logic.

For further learning, explore advanced topics. Study account abstraction (ERC-4337) and user operations for more flexible transaction batching. Analyze how major protocols like Yearn Finance or Balancer orchestrate complex, multi-contract strategies in their vaults. Continuously monitor EIPs and client updates (e.g., Geth, Erigon) that affect gas pricing and call execution. The landscape evolves rapidly, and staying informed is crucial for maintaining optimized and secure call structures in production.