Taiko - K42's results

Gas Optimization Report for Taiko by K42

Possible Optimizations in TaikoGovernor.sol

Possible Optimization 1 =

• The supportsInterface() function performs multiple inheritance checks using super. Inlining these checks can reduce the overhead associated with external function calls.

Here is the optimized code snippet:

// Before Optimization
function supportsInterface(bytes4 _interfaceId)
    public
    view
    override(GovernorUpgradeable, GovernorTimelockControlUpgradeable, IERC165Upgradeable)
    returns (bool)
{
    return super.supportsInterface(_interfaceId);
}

// After Optimization
function supportsInterface(bytes4 _interfaceId)
    public
    view
    override(GovernorUpgradeable, GovernorTimelockControlUpgradeable, IERC165Upgradeable)
    returns (bool)
{
    return _interfaceId == type(IGovernorUpgradeable).interfaceId
        || _interfaceId == type(GovernorTimelockControlUpgradeable).interfaceId
        || _interfaceId == type(IERC165Upgradeable).interfaceId;
}

• Estimated gas saved = This change could save gas by avoiding multiple JUMP operations in the EVM for each inheritance chain call. The savings might be around 200 or more gas per supportsInterface call, depending on the EVM's current gas pricing for these operations.

Possible Optimization 2 =

• Functions like votingDelay(), votingPeriod(), and proposalThreshold() are marked as public and pure, meaning they do not read from or modify state and return a constant value. These functions can also be inlined where used to save gas on external function calls.

Here is the optimized code:

// Instead of calling votingDelay(), directly use its return value where needed
uint256 votingDelay = 7200; // Use the constant value directly

// Apply similar inlining for votingPeriod() and proposalThreshold()

• Estimated gas saved = Directly using the constant values instead of function calls can save around 200 or so gas per call, depending on where and how often these functions are called.

Possible Optimizations in AssignmentHook.sol

Possible Optimization 1 =

• The _getProverFee() function iterates over the tierFees array to find the fee associated with a given tier. This can be optimized by using a mapping for direct access if the tiers are known and relatively static, or by ensuring the array is sorted and implementing a binary search for dynamic cases.

Here is the optimized code snippet:

// Assuming tiers are static and known, replace the array with a mapping for direct access.
// This requires changes in how tierFees are stored and accessed throughout the contract.
mapping(uint16 => uint256) private _tierFees;

function _setProverFee(uint16 _tierId, uint256 _fee) internal {
    _tierFees[_tierId] = _fee;
}

function _getProverFee(uint16 _tierId) private view returns (uint256) {
    require(_tierFees[_tierId] != 0, "HOOK_TIER_NOT_FOUND");
    return _tierFees[_tierId];
}

• Estimated gas saved = This change could save gas by reducing the computational complexity of the tier fee lookup from O(n) to O(1). The exact savings would depend on the number of tiers typically involved in a lookup.

Possible Optimization 2 =

• The contract makes multiple calls to resolve and msg.sender for fetching contract addresses (e.g., taiko_token, taikoL1Address). Caching these addresses after the first lookup or initialization could save gas on subsequent accesses.

Here is the optimized code:

address private _taikoTokenAddress;
address private _taikoL1Address;

function _cacheAddresses() internal {
    if (_taikoTokenAddress == address(0)) {
        _taikoTokenAddress = resolve("taiko_token", false);
    }
    if (_taikoL1Address == address(0)) {
        _taikoL1Address = msg.sender; // Assuming msg.sender is always the TaikoL1 contract after the first call
    }
}

// Use _taikoTokenAddress and _taikoL1Address directly in the function calls instead of resolving them each time

• Estimated gas saved = This change could save a few hundred to a few thousand gas per transaction, depending on how frequently these addresses are accessed within a single transaction.

Possible Optimizations in LibProposing.sol

Possible Optimization 1 =

• The contract frequently resolves addresses using the _resolver parameter, which can be gas-intensive due to external calls. Caching these addresses after the first resolution within a function call can save gas.

• Optimized Code Snippet:

function proposeBlock(
    TaikoData.State storage _state,
    TaikoData.Config memory _config,
    IAddressResolver _resolver,
    bytes calldata _data,
    bytes calldata _txList
)
    internal
    returns (TaikoData.BlockMetadata memory meta_, TaikoData.EthDeposit[] memory deposits_)
{
    // Cache resolved addresses
    address taikoTokenAddress = _resolver.resolve("taiko_token", false);
    address tierProviderAddress = _resolver.resolve("tier_provider", false);

    // Use cached addresses in the function
    ...
}

• Estimated Gas Saved: This optimization could save hundreds to thousands of gas per transaction, depending on the frequency of address resolution within the function.

Possible Optimization 2 =

• The contract performs many conditional checks in a sequence that could be optimized by combining related conditions and exiting early where possible.

• Optimized Code Snippet:

function proposeBlock(
    ...
)
    internal
    returns (TaikoData.BlockMetadata memory meta_, TaikoData.EthDeposit[] memory deposits_)
{
    ...
    // Combine related conditional checks for efficiency
    if (params.assignedProver == address(0) || !LibAddress.isSenderEOA()) {
        revert L1_INVALID_PROVER();
    }

    // Early exit if unauthorized or too many blocks
    if (!_isProposerPermitted(b, _resolver) || b.numBlocks >= b.lastVerifiedBlockId + _config.blockMaxProposals + 1) {
        revert L1_UNAUTHORIZED();
    }
    ...
}

• Estimated Gas Saved: This change could save a small amount of gas by reducing the number of conditional checks and leveraging short-circuit evaluation. The savings might be modest but improve clarity and efficiency.

Possible Optimization 3 =

• The logic for reusing blob hashes involves several conditional checks that can be streamlined. Specifically, the checks for blob reuse and caching can be optimized to reduce redundancy.

• Optimized Code Snippet:

// Simplify blob reuse and caching logic
if (meta_.blobUsed && _config.blobAllowedForDA) {
    if (params.blobHash != 0 && _config.blobReuseEnabled && isBlobReusable(_state, _config, params.blobHash)) {
        meta_.blobHash = params.blobHash;
    } else if (params.blobHash == 0) {
        meta_.blobHash = blobhash(0);
        if (meta_.blobHash == 0) revert L1_BLOB_NOT_FOUND();
    }

    if (params.cacheBlobForReuse) {
        _state.reusableBlobs[meta_.blobHash] = block.timestamp;
        emit BlobCached(meta_.blobHash);
    }
}

• Estimated Gas Saved: By simplifying the blob reuse logic, this optimization could save gas by reducing the complexity and number of storage operations involved. The exact savings would depend on the frequency of blob reuse and caching operations.

Possible Optimizations in LibProving.sol

Possible Optimization 1 =

• The contract performs multiple checks on the tier of proofs, which can be streamlined to reduce gas usage.

Here is the optimized code snippet:

// Replace repetitive tier checks with a single call to _checkTierValidity where applicable.
function _checkTierValidity(TaikoData.TierProof memory _proof, uint16 _minTier, ITierProvider.Tier memory _tier) private pure {
    require(_proof.tier != 0 && _proof.tier >= _minTier, "L1_INVALID_TIER");
    require(_tier.contestBond != 0, "L1_MISSING_VERIFIER");
}

• Estimated gas saved = This optimization could save a few hundred gas per transaction by reducing the number of conditional checks and leveraging short-circuit evaluation.

Possible Optimization 2 =

• The logic for updating transition states, especially when handling contests and proofs, involves multiple storage operations that can be optimized.

Here is the optimized code:

// Replace repetitive state updates with a single call to _updateTransitionState where applicable.
function _updateTransitionState(
    TaikoData.TransitionState storage _ts,
    TaikoData.Transition memory _tran,
    TaikoData.TierProof memory _proof,
    bool _isContesting,
    uint256 _contestBond,
    address _prover
) private {
    _ts.prover = _prover;
    _ts.blockHash = _tran.blockHash;
    _ts.stateRoot = _tran.stateRoot;
    _ts.tier = _proof.tier;
    if (_isContesting) {
        _ts.contestBond = _contestBond;
        _ts.contester = msg.sender;
    }
}

• Estimated gas saved = This change could save gas by reducing the number of SSTORE operations, especially in functions with multiple conditional paths. The exact savings would depend on the frequency and pattern of state updates.

Possible Optimizations in LibVerifying.sol

Possible Optimization 1 =

• Simplify the _isConfigValid() function by grouping related conditions and using intermediate variables for clarity and potentially reducing gas costs due to less repeated access to struct properties.

Here is the optimized code snippet:

function _isConfigValid(TaikoData.Config memory _config) private pure returns (bool) {
    bool isValidChainId = _config.chainId > 1 && _config.chainId != block.chainid;
    bool isValidBlockSettings = _config.blockMaxProposals > 1 &&
                                _config.blockRingBufferSize > _config.blockMaxProposals + 1 &&
                                _config.blockMaxGasLimit > 0 && 
                                _config.blockMaxTxListBytes > 0 &&
                                _config.blockMaxTxListBytes <= 128 * 1024; // Up to 128K
    bool isValidDepositSettings = _config.ethDepositRingBufferSize > 1 &&
                                  _config.ethDepositMinCountPerBlock > 0 &&
                                  _config.ethDepositMaxCountPerBlock <= 32 &&
                                  _config.ethDepositMaxCountPerBlock >= _config.ethDepositMinCountPerBlock &&
                                  _config.ethDepositMinAmount > 0 &&
                                  _config.ethDepositMaxAmount > _config.ethDepositMinAmount &&
                                  _config.ethDepositMaxAmount <= type(uint96).max &&
                                  _config.ethDepositGas > 0 &&
                                  _config.ethDepositMaxFee > 0 &&
                                  _config.ethDepositMaxFee <= type(uint96).max / _config.ethDepositMaxCountPerBlock;

    return isValidChainId && isValidBlockSettings && isValidDepositSettings && _config.livenessBond > 0;
}

• Estimated gas saved = This optimization could save gas by reducing the complexity of condition checks and minimizing the number of operations. The exact savings would depend on the EVM's current gas pricing for these operations.

Possible Optimization 2 =

• Reduce the number of storage reads within the loop of verifyBlocks() by caching frequently accessed values and minimizing redundant resolver calls

Here is the optimized code:

function verifyBlocks(
    TaikoData.State storage _state,
    TaikoData.Config memory _config,
    IAddressResolver _resolver,
    uint64 _maxBlocksToVerify
)
    internal
{
    if (_maxBlocksToVerify == 0) return;

    address tierProvider = _resolver.resolve("tier_provider", false);
    IERC20 tko = IERC20(_resolver.resolve("taiko_token", false));
    uint64 numBlocksVerified = 0;
    uint64 blockId = _state.slotB.lastVerifiedBlockId + 1;

    while (blockId < _state.slotB.numBlocks && numBlocksVerified < _maxBlocksToVerify) {
        uint64 slot = blockId % _config.blockRingBufferSize;
        TaikoData.Block storage blk = _state.blocks[slot];
        if (blk.blockId != blockId) break;

        uint32 tid = blk.verifiedTransitionId;
        if (tid == 0) break;

        TaikoData.TransitionState storage ts = _state.transitions[slot][tid];
        if (ts.contester != address(0)) break;

        ITierProvider.Tier memory tier = ITierProvider(tierProvider).getTier(ts.tier);
        if (uint256(tier.cooldownWindow) * 60 + uint256(ts.timestamp).max(_state.slotB.lastUnpausedAt) > block.timestamp) break;

        // Proceed with verification logic...
        ++numBlocksVerified;
        blockId = _state.slotB.lastVerifiedBlockId + numBlocksVerified;
    }

    if (numBlocksVerified > 0) {
        _state.slotB.lastVerifiedBlockId += numBlocksVerified;
        // Additional logic for syncing chain data...
    }
}

• Estimated gas saved = By caching the tierProvider and tko addresses outside the loop and reducing the number of resolver calls, this optimization could save a significant amount of gas, especially in loops with multiple iterations. The savings would be more pronounced in scenarios with a higher number of blocks verified in a single transaction.

Possible Optimizations in TaikoData.sol

Possible Optimization =

• How you order your struct's variables can affect gas costs, especially when these structs are frequently written to or updated. For TaikoData structs, ensuring that smaller data types are packed together can minimize the number of storage slots used.

Here is the optimized code snippet:

struct BlockMetadata {
    bytes32 l1Hash; // slot 1
    bytes32 difficulty; // slot 2
    bytes32 blobHash; // slot 3
    bytes32 extraData; // slot 4
    bytes32 depositsHash; // slot 5
    bytes32 parentMetaHash; // slot 8
    address coinbase; // slot 6
    uint64 id;
    uint64 timestamp; // slot 7
    uint64 l1Height;
    uint32 gasLimit;
    uint24 txListByteOffset;
    uint24 txListByteSize;
    uint16 minTier;
    bool blobUsed;
}

• Estimated gas saved = The savings depend on how often these structs are written to or updated. Reordering variables for optimal packing can save thousands of gas over many transactions due to reduced storage operations.

Possible Optimizations in TaikoL1.sol

Possible Optimization 1 =

• The getConfig() function is called multiple times throughout the contract. Since the configuration is unlikely to change often, caching its result at the beginning of functions that use it multiple times can save gas.

Here is the optimized code snippet:

function proposeBlock(bytes calldata _params, bytes calldata _txList)
    external
    payable
    nonReentrant
    whenNotPaused
    returns (TaikoData.BlockMetadata memory meta_, TaikoData.EthDeposit[] memory deposits_)
{
    // Cache the configuration at the start
    TaikoData.Config memory config = getConfig();

    // Use `config` throughout the function...
}

• Estimated gas saved = This optimization could save hundreds to thousands of gas per transaction, depending on the complexity and frequency of getConfig() calls within each transaction.

Possible Optimization 2 =

• The whenProvingNotPaused() modifier checks if proving is paused and reverts if it is. This check could be combined with other state checks in functions to reduce the overhead of modifier invocations.

Here is the optimized code:

function proveBlock(uint64 _blockId, bytes calldata _input)
    external
    nonReentrant
    whenNotPaused
{
    if (state.slotB.provingPaused) revert L1_PROVING_PAUSED();
    // Function logic continues...
}

• Estimated gas saved = Combining state checks into a single conditional statement can save gas by reducing the number of jumps and condition evaluations. The savings might be modest but can improve contract efficiency.

Possible Optimizations in TaikoL2.sol

Possible Optimization 1 =

• The anchor() function reads from storage multiple times to get the configuration and to check the last synced block. Caching these values at the beginning of the function can reduce gas costs associated with storage reads.

Here is the optimized code snippet:

function anchor(
    bytes32 _l1BlockHash,
    bytes32 _l1StateRoot,
    uint64 _l1BlockId,
    uint32 _parentGasUsed
)
    external
    nonReentrant
{
    Config memory config = getConfig(); // Cache config
    uint64 lastSynced = lastSyncedBlock; // Cache last synced block

    // Use `config` and `lastSynced` in the function...
}

• Estimated gas saved = Caching storage variables can save hundreds to thousands of gas per transaction, depending on the number of reads avoided.

Possible Optimization 2 =

• The _calc1559BaseFee() function performs several arithmetic operations and conditionals that can be streamlined for efficiency.

• Optimized Code Snippet:

  function _calc1559BaseFee(
      Config memory _config,
      uint64 _l1BlockId,
      uint32 _parentGasUsed
  )
      private
      view
      returns (uint256 basefee_, uint64 gasExcess_)
  {
      uint256 excess = uint256(gasExcess).add(_parentGasUsed);
      uint256 numL1Blocks = _l1BlockId > lastSyncedBlock ? _l1BlockId - lastSyncedBlock : 0;
      uint256 issuance = numL1Blocks.mul(_config.gasTargetPerL1Block);
      excess = excess > issuance ? excess.sub(issuance) : 1;
      gasExcess_ = uint64(excess);
      basefee_ = Lib1559Math.basefee(gasExcess_, _config.basefeeAdjustmentQuotient.mul(_config.gasTargetPerL1Block));
      if (basefee_ == 0) basefee_ = 1;
  }

• Estimated Gas Saved = By simplifying arithmetic operations and conditionals, this optimization could save gas by reducing the computational overhead. The savings would be more pronounced in scenarios where this function is called frequently.

Possible Optimizations in SignalService.sol

Possible Optimization 1 =

• The contract frequently accesses storage variables such as isAuthorized, topBlockId, and signal slots. Caching these values in memory when they are accessed more than once in a function can save gas.

• Optimized Code Snippet:

  function syncChainData(
      uint64 _chainId,
      bytes32 _kind,
      uint64 _blockId,
      bytes32 _chainData
  )
      external
      returns (bytes32)
  {
      // Cache authorization status to reduce storage access
      bool authorized = isAuthorized[msg.sender];
      if (!authorized) revert SS_UNAUTHORIZED();
  
      // Proceed with the rest of the function...
  }

• Estimated Gas Saved = This optimization can save a few hundred gas per transaction by avoiding repeated SLOAD operations.

Possible Optimization 2 =

• The proveSignalReceived() function performs multiple operations that could be optimized. For example, verifying hop proofs and caching chain data involve repeated patterns that could be abstracted into internal functions to reduce code duplication and potentially optimize gas usage.

• Optimized Code Snippet:

  function proveSignalReceived(
      uint64 _chainId,
      address _app,
      bytes32 _signal,
      bytes calldata _proof
  )
      public
      validSender(_app)
      nonZeroValue(_signal)
  {
      HopProof[] memory hopProofs = abi.decode(_proof, (HopProof[]));
      if (hopProofs.length == 0) revert SS_EMPTY_PROOF();
  
      // Abstracted logic for verifying hop proofs and caching chain data
      _processHopProofs(hopProofs, _chainId, _app, _signal);
  }
  
  function _processHopProofs(HopProof[] memory hopProofs, uint64 _chainId, address _app, bytes32 _signal) private {
      // Implement the logic for processing hop proofs, verifying them, and caching chain data
      // This abstracts the repeated patterns in the original function
  }

• Estimated Gas Saved = While the exact gas savings depend on the implementation details and the number of hop proofs processed, abstracting repeated logic into internal functions can reduce bytecode size and optimize execution paths, potentially saving gas.

Possible Optimization 3 =

• Emitting events with less frequently used data or combining multiple related events into a single event can reduce gas costs associated with logging.

• Optimized Code Snippet:

  event SignalProcessed(address indexed app, bytes32 indexed signal, bool success);
  
  function _sendSignal(address _app, bytes32 _signal, bytes32 _value) private validSender(_app) nonZeroValue(_signal) nonZeroValue(_value) returns (bytes32 slot_) {
      slot_ = getSignalSlot(uint64(block.chainid), _app, _signal);
      bool success = true;
      // Attempt to store the signal value, set success to false if it fails
      // Simplified for illustration
      assembly { sstore(slot_, _value) }
      emit SignalProcessed(_app, _signal, success);
  }

• Estimated Gas Saved = Reducing the number of events or the amount of data logged in each event can save gas, especially for contracts that emit events frequently. The savings vary based on the size and number of data points in the original events.

Possible Optimizations in Bridge.sol

Possible Optimization 1 =

• The messageStatus mapping is accessed multiple times in various functions to check or update the status of a message. Caching this status can reduce gas costs associated with storage reads.

function processMessage(Message calldata _message, bytes calldata _proof)
    external
    nonReentrant
    whenNotPaused
    sameChain(_message.destChainId)
{
    bytes32 msgHash = hashMessage(_message);
    Status cachedStatus = messageStatus[msgHash]; // Cache the status

    if (cachedStatus != Status.NEW) revert B_STATUS_MISMATCH();

    // Further logic using cachedStatus instead of reading from storage again
}

• Estimated Gas Saved = This change can save a few hundred gas per transaction, especially in functions that perform multiple operations based on the message status.

Possible Optimization 2 =

• Implement a batch processing mechanism for updating message statuses where applicable, especially in admin functions like suspendMessages() or banAddress(). Functions that iterate over arrays to update statuses or ban statuses can benefit from a more efficient batch processing approach to minimize the number of storage operations.

function suspendMessages(bytes32[] calldata _msgHashes, bool _suspend) external onlyFromOwnerOrNamed("bridge_watchdog")
{
    for (uint256 i = 0; i < _msgHashes.length; ++i) {
        bytes32 msgHash = _msgHashes[i];
        Status currentStatus = messageStatus[msgHash];
        Status newStatus = _suspend ? Status.SUSPENDED : Status.NEW; // Define new status based on _suspend flag

        if (currentStatus != newStatus) {
            messageStatus[msgHash] = newStatus; // Update only if status changes
            emit MessageSuspended(msgHash, _suspend);
        }
    }
}

• Estimated Gas Saved = While the direct gas savings per transaction might be modest, this optimization reduces the overall cost of batch operations by minimizing unnecessary storage writes.

Possible Optimizations in BridgedERC20.sol

Possible Optimization 1 =

• The name() and symbol() functions build the token's name and symbol dynamically, potentially including operations that could be optimized or precomputed.

Optimized Code Snippet:

// Precompute the full name and symbol in the init function and store them in storage variables.
string private _fullName;
string private _fullSymbol;

function init(
    address _owner,
    address _addressManager,
    address _srcToken,
    uint256 _srcChainId,
    uint8 _decimals,
    string memory _symbol,
    string memory _name
) external initializer {
    // Existing initialization logic...
    _fullName = LibBridgedToken.buildName(_name, _srcChainId);
    _fullSymbol = LibBridgedToken.buildSymbol(_symbol);
}

function name() public view override returns (string memory) {
    return _fullName;
}

function symbol() public view override returns (string memory) {
    return _fullSymbol;
}

• Estimated Gas Saved = This change could save gas on each call to name and symbol by avoiding dynamic string concatenation and computation. The savings would be more significant in contracts where these functions are called frequently.

Possible Optimization 2 =

• The onlyOwnerOrSnapshooter modifier checks if the caller is the owner or the snapshooter. This check could be optimized by reducing the number of external calls if the owner is stored in a state variable that can be directly accessed.

Optimized Code Snippet:

modifier onlyOwnerOrSnapshooter() {
    address _owner = owner(); // Assuming owner() is a function call that might be optimized if owner is stored in a state variable directly
    require(msg.sender == _owner || msg.sender == snapshooter, "BTOKEN_UNAUTHORIZED");
    _;
}

• Estimated Gas Saved = This optimization might save a small amount of gas per transaction that uses this modifier by reducing the number of function calls if owner() is optimized. The savings would be minor per transaction but could add up over many transactions.

Possible Optimizations in ERC1155Vault.sol

Possible Optimization 1 =

• When sending tokens, the contract iterates over arrays to check amounts and perform transfers. This process can be optimized by reducing redundant checks and leveraging batch operations provided by the ERC1155 standard more effectively.

• Optimized Code Snippet:

  function sendToken(BridgeTransferOp memory _op)
      external
      payable
      nonReentrant
      whenNotPaused
      withValidOperation(_op)
      returns (IBridge.Message memory message_)
  {
      require(_op.amounts.length > 0, "VAULT_INVALID_AMOUNT");
      require(_op.token.supportsInterface(ERC1155_INTERFACE_ID), "VAULT_INTERFACE_NOT_SUPPORTED");
  
      IERC1155(_op.token).safeBatchTransferFrom(msg.sender, address(this), _op.tokenIds, _op.amounts, "");
  
      // Remaining logic for message creation and event emission...
  }

• Estimated Gas Saved = Leveraging safeBatchTransferFrom directly for all token IDs and amounts in one call significantly reduces the gas cost by minimizing the number of external calls and checks. The exact savings depend on the number of tokens being transferred.

Possible Optimization 2 =

• The contract frequently resolves addresses using the resolve() function, which can be gas-intensive due to potential storage reads. Caching these addresses at the beginning of functions that use them multiple times can save gas.

• Optimized Code Snippet:

  function sendToken(BridgeTransferOp memory _op)
      external
      payable
      nonReentrant
      whenNotPaused
      withValidOperation(_op)
      returns (IBridge.Message memory message_)
  {
      address bridgeAddress = resolve("bridge", false);
      address tokenAddress = resolve(_op.destChainId, name(), false);
  
      // Use `bridgeAddress` and `tokenAddress` in the function...
  }

• Estimated Gas Saved = Caching resolved addresses can save hundreds to thousands of gas per transaction, depending on the number of reads avoided and the complexity of the resolve function.

Possible Optimization 3 =

• The _getOrDeployBridgedToken() function checks if a bridged token exists and deploys one if it doesn't. This process can be optimized by reducing the number of storage reads and writes.

• Optimized Code Snippet:

  function _getOrDeployBridgedToken(CanonicalNFT memory _ctoken) private returns (address btoken_) {
      btoken_ = canonicalToBridged[_ctoken.chainId][_ctoken.addr];
      if (btoken_ == address(0)) {
          btoken_ = _deployBridgedToken(_ctoken);
          bridgedToCanonical[btoken_] = _ctoken;
          canonicalToBridged[_ctoken.chainId][_ctoken.addr] = btoken_;
          emit BridgedTokenDeployed(_ctoken.chainId, _ctoken.addr, btoken_, _ctoken.symbol, _ctoken.name);
      }
  }

• Estimated Gas Saved = This optimization minimizes storage operations by ensuring that token deployment and mapping updates are only performed when necessary. The savings are more pronounced when frequently interacting with the same set of tokens.

Possible Optimizations in ERC20Vault.sol

Possible Optimization 1 =

• For sendToken() consolidate token amount and blacklist checks, into a single loop to minimize redundant operations and storage accesses.

• Optimized Code Snippet:

function sendToken(BridgeTransferOp calldata _op)
    external
    payable
    nonReentrant
    whenNotPaused
    returns (IBridge.Message memory message_)
{
    require(_op.amount > 0, "VAULT_INVALID_AMOUNT");
    require(_op.token != address(0), "VAULT_INVALID_TOKEN");
    require(!btokenBlacklist[_op.token], "VAULT_BTOKEN_BLACKLISTED");

    // Proceed with token transfer logic...
}

• Estimated Gas Saved = This optimization reduces the gas cost by avoiding multiple require checks for each token in the _op.amounts array. The exact savings depend on the size of the array and the frequency of transactions.

Possible Optimization 2 =

• Cache frequently used resolved addresses at the beginning of functions to reduce redundant calls to the resolve function.

• Optimized Code Snippet:

function sendToken(BridgeTransferOp calldata _op)
    external
    payable
    nonReentrant
    whenNotPaused
    returns (IBridge.Message memory message_)
{
    address bridgeAddress = resolve("bridge", false);
    address tokenAddress = resolve(_op.destChainId, name(), false);

    // Use `bridgeAddress` and `tokenAddress` throughout the function...
}

• Estimated Gas Saved = Caching resolved addresses can save hundreds to thousands of gas per transaction, depending on the complexity of the resolve function and the number of times it's called within a transaction.

Possible Optimization 3 =

• For _getOrDeployBridgedToken(), optimize the logic for deploying bridged tokens and updating mappings, to reduce storage operations and improve code efficiency.

• Optimized Code Snippet:

function _getOrDeployBridgedToken(CanonicalERC20 memory ctoken)
    private
    returns (address btoken)
{
    btoken = canonicalToBridged[ctoken.chainId][ctoken.addr];
    if (btoken == address(0)) {
        btoken = _deployBridgedToken(ctoken);
        canonicalToBridged[ctoken.chainId][ctoken.addr] = btoken;
        bridgedToCanonical[btoken] = ctoken;
        emit BridgedTokenDeployed(ctoken.chainId, ctoken.addr, btoken, ctoken.symbol, ctoken.name, ctoken.decimals);
    }
}

• Estimated Gas Saved = This optimization minimizes the number of storage writes by ensuring that token deployment and mapping updates are only performed when necessary. The savings are more pronounced when interacting frequently with the same set of tokens.

Possible Optimizations in ERC721Vault.sol

Possible Optimization 1 =

• For sendToken() here also, simplify and batch token transfer checks to minimize redundant operations.

• Code Snippet:

function sendToken(BridgeTransferOp memory _op)
    external
    payable
    nonReentrant
    whenNotPaused
    returns (IBridge.Message memory message_)
{
    require(_op.token.supportsInterface(ERC721_INTERFACE_ID), "VAULT_INTERFACE_NOT_SUPPORTED");
    for (uint256 i = 0; i < _op.tokenIds.length; ++i) {
        require(_op.amounts[i] == 0, "VAULT_INVALID_AMOUNT");
        IERC721(_op.token).safeTransferFrom(msg.sender, address(this), _op.tokenIds[i]);
    }
    // Proceed with the rest of the function...
}

• Estimated Gas Saved = This optimization reduces the gas cost by eliminating the need for separate checks for each token amount, assuming all amounts should be zero for ERC721 tokens. It consolidates the transfer operation into the loop that already exists, reducing the overhead of separate operations.

Possible Optimization 2 =

• Also for sendToken(), cache frequently used resolved addresses at the beginning of functions to reduce redundant calls to the resolve function.

• Code Snippet:

function sendToken(BridgeTransferOp memory _op)
    external
    payable
    nonReentrant
    whenNotPaused
    returns (IBridge.Message memory message_)
{
    address bridgeAddress = resolve("bridge", false);
    // Use `bridgeAddress` throughout the function...
}

• Estimated Gas Saved = Caching resolved addresses can save hundreds to thousands of gas per transaction, depending on the complexity of the resolve function and the number of times it's called within a transaction.

Possible Optimization 3 =

• For _getOrDeployBridgedToken(), streamline the logic for deploying bridged tokens and updating mappings to reduce storage operations and improve code efficiency.

• Optimized code:

function _getOrDeployBridgedToken(CanonicalNFT memory _ctoken)
    private
    returns (address btoken_)
{
    btoken_ = canonicalToBridged[_ctoken.chainId][_ctoken.addr];
    if (btoken_ == address(0)) {
        btoken_ = _deployBridgedToken(_ctoken);
        bridgedToCanonical[btoken_] = _ctoken;
        canonicalToBridged[_ctoken.chainId][_ctoken.addr] = btoken_;
        // Emit event here if necessary
    }
}

• Estimated Gas Saved = This optimization minimizes the number of storage writes by ensuring that token deployment and mapping updates are only performed when necessary. The savings are more pronounced when interacting frequently with the same set of tokens.

Possible Optimizations in RLPReader.sol

Possible Optimization 1 =

• Minimize the use of inline assembly for operations that can be performed with Solidity's already built-in functions. While assembly can offer gas savings, it also bypasses Solidity's safety checks, increasing the risk of errors.

• Code Snippet:

  // Original assembly code for pointer adjustment
  // assembly {
  //     ptr := add(_in, 32)
  // }
  // Optimized Solidity approach
  MemoryPointer ptr = MemoryPointer.wrap(uint256(uint160(address(_in))) + 32);

• Estimated Gas Saved = This change might not directly result in gas savings. However, it enhances the safety and maintainability of the code, potentially preventing costly errors.

Possible Optimization 2 =

• Optimize the _decodeLength() function by consolidating similar logic branches and removing redundant checks. This can reduce the overall bytecode size and gas usage.

• Code Snippet:

  function _decodeLength(RLPItem memory _in)
      private
      pure
      returns (uint256 offset_, uint256 length_, RLPItemType type_)
  {
      // Simplify the prefix checks and combine similar logic paths
      uint256 prefix = uint256(uint8(_in.ptr[0]));
      if (prefix <= 0x7f) {
          return (0, 1, RLPItemType.DATA_ITEM);
      } else if (prefix <= 0xbf) {
          // Combine short and long string logic
          uint256 lenOfStrLen = (prefix <= 0xb7) ? 1 : prefix - 0xb7;
          uint256 strLen = (prefix <= 0xb7) ? prefix - 0x80 : uint256(uint8(_in.ptr[lenOfStrLen]));
          return (lenOfStrLen, strLen, RLPItemType.DATA_ITEM);
      } else {
          // Combine short and long list logic
          uint256 lenOfListLen = (prefix <= 0xf7) ? 1 : prefix - 0xf7;
          uint256 listLen = (prefix <= 0xf7) ? prefix - 0xc0 : uint256(uint8(_in.ptr[lenOfListLen]));
          return (lenOfListLen, listLen, RLPItemType.LIST_ITEM);
      }
  }

• Estimated Gas Saved = This optimization could save gas by reducing the complexity and size of the _decodeLength function. The exact savings depend on how frequently this function is called and the distribution of RLP item types it processes.

Possible Optimization 3 =

• When reading RLP lists, dynamically adjust the size of the output array based on the actual number of items, rather than using a fixed maximum size.

• Code Snippet:

  function readList(RLPItem memory _in) internal pure returns (RLPItem[] memory out_) {
      // Existing logic to determine list length and item count...
      out_ = new RLPItem[](itemCount); // Allocate memory based on actual item count
      // Populate the `out_` array with RLP items...
  }

• Estimated Gas Saved = This change can significantly reduce gas costs associated with memory allocation and unused array space. The savings vary based on the actual number of items in RLP lists being processed.

Possible Optimizations in MerkleTrie.sol

Possible Optimization 1 =

• For _parseProof() reduce the overhead of repeatedly decoding RLP items during proof parsing by directly accessing the decoded data when possible.

• Code Snippet:

  function _parseProof(bytes[] memory _proof) private pure returns (TrieNode[] memory proof_) {
      uint256 length = _proof.length;
      proof_ = new TrieNode[](length);
      for (uint256 i = 0; i < length; i++) {
          bytes memory encoded = _proof[i];
          RLPReader.RLPItem[] memory decoded = RLPReader.readList(encoded);
          proof_[i] = TrieNode({ encoded: encoded, decoded: decoded });
      }
  }

• Estimated Gas Saved = This change itself may not directly save a significant amount of gas per operation but improves code clarity and potentially reduces computational redundancy, indirectly affecting gas usage.

Possible Optimization 2 =

• Simplify the _getNodeID() function to avoid unnecessary conditional checks and direct manipulation.

• Code Snippet:

  function _getNodeID(RLPReader.RLPItem memory _node) private pure returns (bytes memory id_) {
      // Assuming RLPReader.readRawBytes already handles the length check internally
      id_ = RLPReader.readRawBytes(_node);
  }

• Estimated Gas Saved = This optimization minimizes the execution path and removes redundant checks, potentially saving gas for each node ID generation. The exact savings depend on the frequency and context in which _getNodeID is called.

Possible Optimization 3 =

• Optimize the _getSharedNibbleLength() function to use assembly for loop unrolling and memory access, reducing the overhead of high-level operations.

• Code Snippet:

  // Note: Use of inline assembly can increase complexity and should be used cautiously.
  function _getSharedNibbleLength(bytes memory _a, bytes memory _b) private pure returns (uint256 shared_) {
      assembly {
          let length := mload(_a)
          let minLength := lt(length, mload(_b)) ? length : mload(_b)
          let aPtr := add(_a, 0x20)
          let bPtr := add(_b, 0x20)
  
          for { let i := 0 } lt(i, minLength) { i := add(i, 1) } {
              let aByte := byte(0, mload(add(aPtr, i)))
              let bByte := byte(0, mload(add(bPtr, i)))
              if iszero(eq(aByte, bByte)) { break }
              shared_ := add(shared_, 1)
          }
      }
  }

• Estimated Gas Saved = Using assembly for byte comparison can significantly reduce the gas cost of iterating through byte arrays. However, the savings come with increased code complexity and potential security risks. It's crucial to thoroughly test and review any assembly code.

Possible Optimizations in SgxVerifier.sol

Possible Optimization 1 =

• In _addInstances() perform batch checks for instance registration to minimize redundant storage reads.

• Code Snippet:

  function _addInstances(address[] memory _instances, bool instantValid) private returns (uint256[] memory ids) {
      ids = new uint256[](_instances.length);
      uint64 validSince = uint64(block.timestamp + (instantValid ? 0 : INSTANCE_VALIDITY_DELAY));
  
      for (uint256 i = 0; i < _instances.length; ++i) {
          require(!_instances[i].isZero(), "SGX_INVALID_INSTANCE");
          require(!addressRegistered[_instances[i]], "SGX_ALREADY_ATTESTED");
  
          addressRegistered[_instances[i]] = true;
          uint256 instanceId = nextInstanceId++;
          instances[instanceId] = Instance(_instances[i], validSince);
          ids[i] = instanceId;
  
          emit InstanceAdded(instanceId, _instances[i], address(0), validSince);
      }
  }

• Estimated Gas Saved = Consolidating checks and operations into a single loop reduces the gas cost by minimizing the number of storage reads and writes. The exact savings depend on the number of instances being added.

Possible Optimization 2 =

• Optimize the _isInstanceValid() function by reducing conditional checks and leveraging short-circuit evaluation.

• Code Snippet:

  function _isInstanceValid(uint256 id, address instance) private view returns (bool) {
      Instance memory inst = instances[id];
      return inst.addr == instance && 
             inst.validSince <= block.timestamp && 
             block.timestamp <= inst.validSince + INSTANCE_EXPIRY;
  }

• Estimated Gas Saved = This optimization reduces the computational overhead by directly accessing the instance once and using its cached values for comparison. While the gas savings per call might be minor, it enhances the function's efficiency, especially when called frequently.

Possible Optimization 3 =

• Minimize external calls and redundant data processing in verifyProof() and related functions.

• Code Snippet:

  // Assuming getSignedHash and other related functions are optimized similarly.
  function verifyProof(
      Context calldata _ctx,
      TaikoData.Transition calldata _tran,
      TaikoData.TierProof calldata _proof
  ) external onlyFromNamed("taiko") {
      if (_ctx.isContesting || _proof.data.length != 89) return;
  
      // Simplify signature verification logic here, assuming getSignedHash is optimized.
  }

• Estimated Gas Saved = Streamlining data handling and reducing external calls in critical paths like proof verification can lead to significant gas savings, especially for operations that are executed frequently or involve complex data.

Possible Optimizations in TimelockTokenPool.sol

Possible Optimization 1 =

• Implement batch processing for grant and withdrawal operations to minimize the number of transactions and reduce gas costs associated with repeated contract calls.

• Code Snippet:

  function grantMultiple(address[] calldata _recipients, Grant[] calldata _grants) external onlyOwner {
      require(_recipients.length == _grants.length, "Mismatched arrays");
      for (uint256 i = 0; i < _recipients.length; i++) {
          _grant(_recipients[i], _grants[i]);
      }
  }

• Estimated Gas Saved = This approach can significantly reduce gas costs when granting to multiple recipients by consolidating multiple transactions into a single call. The exact savings depend on the number of grants being processed.

Possible Optimization 2 =

• For _withdraw(), minimize redundant reads from and writes to storage, especially for the mappings and state variables that are frequently accessed.

• Code Snippet:

  function _withdraw(address _recipient, address _to) private {
      Recipient storage r = recipients[_recipient];
      uint128 amountToWithdraw;
      uint128 costToWithdraw;
      (,,, amountToWithdraw, costToWithdraw) = getMyGrantSummary(_recipient);
      // Perform calculations and updates in memory before writing to storage
      r.amountWithdrawn += amountToWithdraw;
      r.costPaid += costToWithdraw;
      // Update storage once after all calculations
      totalAmountWithdrawn += amountToWithdraw;
      totalCostPaid += costToWithdraw;
  }

• Estimated Gas Saved = Reducing the frequency of storage operations can lead to moderate gas savings, especially in functions called frequently by users.

Possible Optimization 3 =

• For _validateGrant(), streamline the grant validation logic to reduce computational overhead and simplify the code.

• Code Snippet:

  function _validateGrant(Grant memory _grant) private pure {
      require(_grant.amount > 0, "INVALID_GRANT");
      require(_grant.grantPeriod > 0, "INVALID_GRANT_PERIOD");
      // Simplify cliff validation based on grant and unlock periods
      require(_grant.grantCliff <= _grant.grantStart + _grant.grantPeriod, "INVALID_GRANT_CLIFF");
      require(_grant.unlockCliff <= _grant.unlockStart + _grant.unlockPeriod, "INVALID_UNLOCK_CLIFF");
  }

• Estimated Gas Saved = While the direct gas savings from simplifying validation logic may be minor, the reduced complexity can lead to fewer errors and more efficient execution.

Possible Optimizations in AutomataDcapV3Attestation.sol

Possible Optimization 1 =

• For addRevokedCertSerialNum(), minimize the number of times mappings are checked for the same condition within a single transaction to reduce gas costs.

Code Snippet:

function addRevokedCertSerialNum(uint256 index, bytes[] calldata serialNumBatch) external onlyOwner {
    for (uint256 i = 0; i < serialNumBatch.length; ++i) {
        bytes memory serialNum = serialNumBatch[i];
        if (!_serialNumIsRevoked[index][serialNum]) {
            _serialNumIsRevoked[index][serialNum] = true;
        }
    }
}

• Estimated Gas Saved = This optimization reduces the gas cost by avoiding redundant checks and storage writes. The savings depend on the size of serialNumBatch.

Possible Optimization 2 =

• For _verifyParsedQuote(), cache values that are frequently accessed from storage, especially when used multiple times within the same function or require complex computations to obtain.

Code Snippet:

function _verifyParsedQuote(V3Struct.ParsedV3QuoteStruct memory v3quote)
    internal
    view
    returns (bool, bytes memory)
{
    EnclaveIdStruct.EnclaveId memory enclaveId = qeIdentity; // Cached for multiple uses within the function
    // Use enclaveId in subsequent operations...
}

• Estimated Gas Saved = Caching reduces the number of expensive storage reads, leading to gas savings, especially in functions called frequently or with complex logic.

Possible Optimizations in PEMCertChainLib.sol

Possible Optimization 1 =

• Optimize the splitCertificateChain() function to reduce string manipulation and improve the efficiency of certificate parsing.

Code Snippet:

function splitCertificateChain(bytes memory pemChain, uint256 size)
    external
    pure
    returns (bool success, bytes[] memory certs)
{
    certs = new bytes[](size);
    uint256 start = 0;
    for (uint256 i = 0; i < size; ++i) {
        uint256 beginPos = pemChain.indexOf(abi.encodePacked(HEADER), start);
        uint256 endPos = pemChain.indexOf(abi.encodePacked(FOOTER), beginPos) + FOOTER_LENGTH;
        if (beginPos == type(uint256).max || endPos == type(uint256).max) {
            return (false, certs);
        }
        certs[i] = pemChain.slice(beginPos + HEADER_LENGTH, endPos - beginPos - HEADER_LENGTH - FOOTER_LENGTH);
        start = endPos;
    }
    return (true, certs);
}

• Estimated Gas Saved = This optimization reduces the computational overhead associated with string manipulations by directly working with byte arrays. The exact gas savings depend on the size of the certificate chain being processed but can be significant for large chains.

Possible Optimization 2 =

• Minimize the number of decoding operations by caching decoded values that are used multiple times within the decodeCert() function.

Code Snippet:

function decodeCert(bytes memory der, bool isPckCert)
    external
    pure
    returns (bool success, ECSha256Certificate memory cert)
{
    // Decode the certificate once and use the decoded values throughout the function
    DecodedCert memory decoded = decodeCertificate(der);
    if (!validateDecodedCert(decoded, isPckCert)) {
        return (false, cert);
    }
    // Use decoded values to populate the cert struct
    cert.serialNumber = decoded.serialNumber;
    cert.notBefore = decoded.notBefore;
    cert.notAfter = decoded.notAfter;
    // Additional logic to populate the cert struct using decoded values
    success = true;
}

• Estimated Gas Saved = By avoiding redundant decoding operations, this optimization can significantly reduce gas costs, especially in functions that are called frequently or process large amounts of data. The savings will vary based on the complexity of the certificates being decoded.

Possible Optimizations in V3Parser.sol

Possible Optimization 1 =

• Reduce the overhead in the parseInput() function by optimizing the handling of byte slices and minimizing redundant operations.

Code Snippet:

function parseInput(bytes memory quote, address pemCertLibAddr)
    internal pure returns (bool success, V3Struct.ParsedV3QuoteStruct memory v3ParsedQuote) {
    if (quote.length <= MINIMUM_QUOTE_LENGTH) {
        return (false, v3ParsedQuote);
    }
    // Directly calculate localAuthDataSize without substring creation
    uint256 localAuthDataSize = littleEndianDecode(quote, 432, 4);
    if (quote.length - 436 != localAuthDataSize) {
        return (false, v3ParsedQuote);
    }
    // Inline parsing operations to avoid unnecessary memory allocations
    success, v3ParsedQuote.header = parseAndVerifyHeader(quote, 0, 48);
    success, v3ParsedQuote.localEnclaveReport = parseEnclaveReport(quote, 48, 384);
    success, v3ParsedQuote.v3AuthData = parseAuthDataAndVerifyCertType(quote, 436, localAuthDataSize, pemCertLibAddr);
    return (success, v3ParsedQuote);
}

• Estimated Gas Saved = This optimization could significantly reduce gas costs by avoiding the creation of temporary byte arrays and directly working with the original byte array. The exact savings would depend on the size of the input data and the frequency of function calls.

Possible Optimization 2 =

• Improve the efficiency of certificate chain parsing by optimizing byte array manipulations and reducing calls to external libraries when possible.

Code Snippet:

function parseCerificationChainBytes(bytes memory certBytes, address pemCertLibAddr)
    internal pure returns (bytes[3] memory certChainData) {
    // Utilize low-level operations for splitting and decoding the certificate chain
    (bool success, bytes[] memory certs) = splitAndDecodeCertificateChain(certBytes, 3);
    require(success, "Certificate chain parsing failed");
    for (uint256 i = 0; i < certs.length; ++i) {
        // Decode each certificate directly if necessary, avoiding redundant library calls
        certChainData[i] = decodeCertificate(certs[i]);
    }
}

• Estimated Gas Saved = By reducing reliance on external library calls for operations that can be performed internally, this optimization can lead to moderate gas savings, especially in contracts where certificate chain parsing is a frequent operation.

Possible Optimizations in Asn1Decode.sol

Possible Optimization 1 =

• Optimize _readNodeLength() by streamlining the process of calculating the length of ASN.1 elements, especially for elements with lengths that can be determined without additional computation.

Code Snippet:

function _readNodeLength(bytes memory der, uint256 ix) private pure returns (uint256) {
    uint256 length;
    uint80 ixFirstContentByte;
    uint80 ixLastContentByte;
    uint8 lengthByte = uint8(der[ix + 1]);

    if (lengthByte < 0x80) {
        length = lengthByte;
        ixFirstContentByte = uint80(ix + 2);
    } else {
        uint8 numLengthBytes = lengthByte & 0x7F;
        length = der.readUintN(ix + 2, numLengthBytes);
        ixFirstContentByte = uint80(ix + 2 + numLengthBytes);
    }
    ixLastContentByte = uint80(ixFirstContentByte + length - 1);
    return NodePtr.getPtr(ix, ixFirstContentByte, ixLastContentByte);
}

• Estimated Gas Saved = This optimization could save gas by reducing the number of operations required to calculate the length of ASN.1 elements, especially for those with direct length specifications. The savings would be more significant in contracts that frequently parse ASN.1 structures.

Possible Optimization 2 =

• Minimize redundant type checks within functions like bitstringAt(), uintAt(), and others by ensuring that these checks are only performed when absolutely necessary or by restructuring the code to avoid unnecessary validations.

Code Snippet:

function bitstringAt(bytes memory der, uint256 ptr) internal pure returns (bytes memory) {
    // Assume type BIT STRING validation is done prior to calling this function
    uint256 valueLength = ptr.ixl() + 1 - ptr.ixf();
    return der.substring(ptr.ixf() + 1, valueLength - 1);
}

• Estimated Gas Saved = By avoiding redundant checks, especially in scenarios where the type of the ASN.1 element has already been validated, this optimization can modestly reduce gas costs. The impact would be more pronounced in parsing operations that are executed frequently within the contract.

Possible Optimizations in BytesUtils.sol

Possible Optimization 1 =

• Reduce the use of inline assembly for operations that Solidity's built-in functions can handle efficiently. While inline assembly can offer direct control over EVM operations and potentially save gas, it also bypasses Solidity's safety checks and can make code harder to read and maintain.

Code Snippet:

function readUint16(bytes memory self, uint256 idx) internal pure returns (uint16 ret) {
    require(idx + 2 <= self.length, "invalid idx");
    ret = uint16(uint8(self[idx])) * 256 + uint16(uint8(self[idx + 1]));
}

• Estimated Gas Saved = This change might not result in significant gas savings directly but enhances code safety and maintainability. Solidity's type conversions and arithmetic operations are highly optimized in recent compiler versions.

Possible Optimization 2 =

• Optimize the substring function to avoid unnecessary memory allocation and copying when the requested substring represents the entire string or a suffix starting from a certain position.

Code Snippet:

function substring(
    bytes memory self,
    uint256 offset,
    uint256 len
)
    internal
    pure
    returns (bytes memory)
{
    require(offset + len <= self.length, "unexpected offset");

    if (offset == 0 && len == self.length) {
        return self;
    }

    bytes memory ret = new bytes(len);
    for (uint256 i = 0; i < len; ++i) {
        ret[i] = self[offset + i];
    }
    return ret;
}

• Estimated Gas Saved = This optimization can save gas by avoiding memory allocation and copying operations when the entire string is requested as a substring. The savings are more pronounced for larger strings or when this operation is called frequently.