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Execution and ordering

Public

How RP1 admits, classifies, orders, and executes transactions while preserving application invariants.

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RP1’s execution path is designed for parallel, observable application work without weakening transaction ownership or deterministic results.

Admission

The lane-aware mempool classifies transactions by type and priority, keeps duplicate indexes synchronized, and preserves accepted work through bounded backpressure. Encrypted and commit-reveal paths exist as experimental, deployment-dependent capabilities; they must not be treated as production cryptographic privacy or enabled for value-bearing workloads without a separately reviewed cryptographic deployment.

The public consequences are:

  • an accepted transaction can remain pending while workers drain;
  • broadcast acknowledgement is not committed finality;
  • transaction ordering is a consensus result, not a client-side sort;
  • gas and fee constraints are checked before execution and preserved in the receipt.

Parallel execution

The application builds a dependency graph from transaction access patterns. Independent transactions can execute in parallel groups; conflicting transactions retain a deterministic order. Module keepers remain responsible for their state invariants, so parallelism is an execution strategy rather than a license to bypass accounting.

MEV-aware execution

RP1 combines transaction lanes, frequent batch auctions, slippage bounds, reference-price checks, and circuit breakers in the production-facing execution model. Encrypted mempool support and commit-reveal remain experimental, deployment-dependent paths and are not a guaranteed MEV shield. Each control protects a different failure mode:

Control Protects against
Encrypted or hidden transaction content Early information leakage in the mempool.
Commit-reveal Revealing order details only after a commitment exists.
Batch auctions Excessive advantage from intra-batch ordering.
Minimum output and price bounds Unacceptable execution price.
Circuit breakers Repeated execution failures or abnormal conditions.

Performance language

The chain repository maintains live benchmark and validator-resource gates. Public docs should report a dated, reproducible run with workload shape, query cadence, validator set, fee, and evidence validity when making a performance claim. Do not use fixture simulations or a single closed-loop run as a universal TPS, finality, or memory guarantee.

Integration implication

Design clients around lifecycle evidence, not timing assumptions. Keep the signed envelope, query by identity, require a positive committed height, and surface unresolved observation separately from execution failure.

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