5.6 KiB
gameplay-flow-regression-coverage Specification
Purpose
Define the required edit-mode regression coverage that protects the MVP gameplay flow from client gameplay input through authoritative server outputs and client-side application.
Requirements
Requirement: Gameplay-flow regressions cover client gameplay send and receive paths
The edit-mode regression suite SHALL cover the MVP client gameplay flow above the raw transport router, including ShootInput send routing and authoritative CombatEvent receive/apply behavior. Lane-policy assertions that belong to MessageManager MAY remain in MessageManagerTests, but gameplay-flow assertions MUST live in tests that exercise the client runtime or player-facing application path.
Scenario: Client fire intent regression proves dedicated ShootInput routing
- WHEN the controlled client gameplay path is exercised in an edit-mode regression test for a fire action
- THEN the test observes a
ShootInputpayload sent through the dedicated client shooting path - THEN any lane-policy assertion in that flow remains limited to confirming the MVP reliable-lane contract rather than replacing broader gameplay-flow coverage
Scenario: Authoritative combat event regression proves client-side application
- WHEN an edit-mode regression test delivers an authoritative
CombatEventinto the client gameplay receive path - THEN the relevant player-owned authoritative state, presentation model, or diagnostics surface reflects the authoritative hit, damage, death, or rejection result
- THEN the test proves the outcome is applied from server truth rather than speculative local combat logic
Requirement: Gameplay-flow regressions cover remote authoritative snapshot decisions
The edit-mode regression suite SHALL cover the client path that buffers and consumes remote authoritative PlayerState snapshots, including stale rejection and interpolation/clamp behavior where practical.
Scenario: Remote interpolation regression proves buffering and stale rejection
- WHEN an edit-mode regression test feeds ordered and stale remote
PlayerStatesnapshots into the client remote-player path - THEN the test observes that newer authoritative snapshots enter the remote buffer while stale snapshots do not replace newer accepted state
- THEN the test verifies the resulting interpolation or latest-snapshot clamp decision matches the MVP remote-presentation rules
Requirement: Gameplay-flow regressions include a fake-transport authoritative round trip
The edit-mode regression suite SHALL include at least one deterministic fake-transport test that spans client send behavior, server-authoritative processing, and outgoing authoritative results. That round-trip regression MUST cover MoveInput -> PlayerState and ShootInput -> CombatEvent within the same MVP gameplay-flow suite, and it MUST assert that authoritative movement stepping follows the configured cadence contract.
Scenario: Fake-transport round trip preserves server authority across movement and combat
- WHEN an edit-mode regression test drives gameplay input through fake client/server transports and advances the server authority loop
- THEN the authoritative server path emits
PlayerStatesnapshots in response to movement input using the configured authoritative movement cadence - THEN the authoritative server path emits
CombatEventresults in response to shooting input - THEN the combined test protects both client single-session input flow and server multi-session authoritative behavior from regression
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