2.1 KiB
2.1 KiB
MODIFIED Requirements
Requirement: Gameplay-flow regressions cover controlled-player correction decisions
The edit-mode regression suite SHALL cover the controlled-player reconciliation path after authoritative movement replay, including bounded correction for small cadence-aligned error, correction replacement under consecutive authoritative snapshots, and hard snap fallback for large or non-convergent divergence.
Scenario: Controlled-player reconciliation uses bounded correction for small error
- WHEN an edit-mode regression test applies an authoritative local
PlayerStatethat leaves only small post-replay divergence - THEN the controlled-player path keeps authoritative ownership of the snapshot
- THEN visible correction converges without an immediate hard snap on the acceptance frame
Scenario: Controlled-player reconciliation updates active correction on repeated small snapshots
- WHEN an edit-mode regression test feeds multiple authoritative local
PlayerStateupdates whose residual divergence remains inside bounded-correction limits while a prior correction is still active - THEN the controlled-player path replaces or folds the active correction according to the sync strategy
- THEN the test proves the client does not accumulate multiple stale correction tails
Scenario: Controlled-player reconciliation snaps on large divergence
- WHEN an edit-mode regression test applies an authoritative local
PlayerStatethat leaves divergence beyond the configured snap threshold - THEN the controlled-player path immediately applies the authoritative transform state
- THEN later prediction resumes from that authoritative baseline
Scenario: Controlled-player reconciliation snaps after failed convergence
- WHEN an edit-mode regression test feeds consecutive authoritative local
PlayerStateupdates that keep bounded correction from converging within the configured budget - THEN the controlled-player path escalates to a hard snap
- THEN the active correction state is cleared before later local prediction continues