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client-prediction-replay Specification

Purpose

Define the contract that client-side replay of pending movement inputs after authoritative state acknowledgement uses fixed-step substeps matching the server authoritative movement cadence, not a single accumulated duration, so that replay trajectory matches live prediction trajectory for the same input sequence.

ADDED Requirements

Requirement: Replay uses fixed-step accumulation matching server cadence

The controlled-client prediction replay path SHALL consume each pending PredictedMoveStep by applying its input in fixed-duration substeps equal to the server authoritative movement cadence, regardless of the step's total SimulatedDurationSeconds. The replay accumulation shape MUST be identical to the live FixedUpdate prediction path for the same input values.

Scenario: Replay produces same trajectory as live prediction for steady input

WHEN the client replays a PredictedMoveStep with turn=0, throttle=1, duration=0.15s using a 0.05s server cadence
THEN the replay applies 0.05s + 0.05s + 0.05s substeps in sequence
THEN the final predicted position matches the position that would result from three consecutive FixedUpdate predictions of 0.05s each with the same input

Scenario: Replay produces same trajectory as live prediction for turn-and-move input

WHEN the client replays a PredictedMoveStep with turn=0.5, throttle=1, duration=0.10s using a 0.05s server cadence
THEN the replay applies two 0.05s substeps where each substep's heading affects the next substep's forward direction
THEN the final predicted heading and position match the live prediction path for the same input sequence

Scenario: Replay handles non-multiples of cadence interval

WHEN the client replays a PredictedMoveStep with duration=0.12s using a 0.05s cadence
THEN the replay applies 0.05s + 0.05s + 0.02s substeps sequentially
THEN no remaining duration is lost or double-counted

Requirement: Replay trajectory determinism is verifiable

The client prediction system SHALL provide a deterministic way to verify that replay and live prediction produce identical trajectories for a given input sequence, enabling regression coverage.

Scenario: Replay and live prediction produce identical results

WHEN a controlled client records a MoveInput sequence during live play
AND the client triggers reconciliation and replays those same inputs
THEN the final predicted pose after replay equals the predicted pose that would result from live FixedUpdate simulation for the same input sequence
THEN the result is stable across multiple replays of the same input sequence

2.7 KiB Raw Blame History