Performance Optimization

Practical recommendations to improve gas efficiency and performance for MetaTxGateway and related contracts.

High-level strategies

• Reduce external calls and on-chain computations where possible.

• Favor calldata over memory for read-only arrays.

• Batch operations to amortize per-transaction overhead.

Specific optimizations

1. Use calldata for input arrays

   • Functions that accept arrays (metaTxs) should use calldata to save gas.

2. Minimize storage writes

   • Only write to storage when necessary (e.g., increment nonces once per batch).

   • Group storage writes to reduce SSTORE overhead.

3. Event design

   • Emit concise events. Emit aggregate events for batches rather than excessive per-call logging if history needs permit.

4. Packing and types

   • Pack booleans and small integers into single storage slots where applicable.

   • Use indexed fields in events selectively (up to 3 indexes).

5. Gas-aware external calls

   • When invoking user-target contracts, avoid specifying large gas limits; allow call to use gasleft().

   • Use try-catch patterns to avoid bubbling errors that cause full revert when partial success is desired.

6. Reserve gas for cleanup

   • When calling external contracts from within try-catch, reserve a small gas buffer for state updates and refunds.

7. Offload heavy work off-chain

   • Signature aggregation, batch building, pre-validation, and retries should be handled by relayers or services off-chain.

8. Benchmark and iterate

   • Use mainnet forks and measure gas for representative batches.

   • Keep a regression test for gas usage to detect accidental regressions.

Example: Packing results

• Instead of returning bool[] in storage, compress results into a bitfield for on-chain summaries and expand off-chain when needed.

Tools & Measurement

• Hardhat gas reporter and profiler.

• Tenderly or block explorer transaction traces for real-time analysis.

• OpenZeppelin Contracts-like audit tools to find costly patterns.

Trade-offs

• Aggressive optimization may reduce readability and maintainability. Prefer clear code with targeted optimizations in hot paths.