⚠️ This is a condensed version of the article.
👉 Read the full, updated version (canonical):
This version summarises the regression testing workflow. The full article includes deeper QA examples, structured analysis, and full case study context.
TL;DR: regression testing in game QA
- Workflow: risk-based regression testing → golden-path baseline → targeted checks → evidence-backed results
- Example context: Sworn (PC Game Pass, Windows)
-
Build tested:
1.01.0.1039 - Scope driver: external patch notes used as a change signal (no platform parity assumed)
- Outputs: regression matrix, session logs, bug tickets, and supporting QA evidence
Regression testing workflow used to verify stability after change during a timeboxed Sworn (PC) pass.
What regression testing is in game QA
Regression testing in game QA verifies that existing behaviour still works after a change.
It is not about re-testing everything or blindly following a checklist.
A practical regression testing workflow is selective and driven by risk:
- what changed
- what might be affected
- what is expensive if broken
- what must remain stable
This is why regression testing is best treated as change-driven verification, not checklist execution.
Golden path baseline in regression testing
Every regression cycle starts with a repeatable golden-path smoke test.
In this example:
BL-SMOKE-01
cold launch → main menu → gameplay → quit → relaunch → main menu
I also include a quick audio sanity check during this flow.
If the golden path is unstable, deeper regression testing becomes unreliable.
Risk-based regression testing and change signals
Regression testing scope is driven by change signals.
In this example, I used public SteamDB patch notes:
SWORN 1.0 Patch #3 (v1.0.3.1111)
Important:
- I did not assume platform parity
- I used patch notes only as a risk signal
This approach is useful in manual QA when internal data is unavailable.
Regression testing matrix example (manual QA)
A regression testing matrix should be auditable.
Each line includes:
- test check
- side-effect probe
- outcome
- evidence
Example checks:
-
BL-SMOKE-01baseline -
BL-SAVE-01save/continue integrity -
STEA-103-MUSICaudio continuity -
STEA-103-AVOLsettings presence -
BL-IO-01input handover -
BL-ALT-01Alt+Tab behaviour
The goal is clear, reviewable results, not assumptions.
Save/Continue regression testing with anchors
Save systems are a high-risk regression area.
To verify reliably, I use anchors:
- location (Wirral Forest)
- health (
60/60) - weapon type
- objective text
These are checked after:
- menu Continue
- full relaunch
This turns vague results into repeatable verification.
QA evidence in regression testing
Regression testing requires evidence for both pass and fail results.
I capture:
- video clips (input, timing, outcome)
- screenshots (UI state, presence/absence)
- session timestamps
- environment details (platform, build, input, saves)
If results cannot be verified, they are not useful.
Example regression bug (game QA)
SWOR-6: Defeat overlay blocks Stats screen
- Expected: Stats screen appears after Continue
- Actual: overlay remains, Stats hidden, new run starts
- Result: Stats cannot be reviewed
- Repro: 3/3
This shows how regression testing surfaces flow-breaking issues after change.
Example regression probe
Patch notes referenced a music fix.
Test:
STEA-103-MUSIC
- 10 minutes runtime
- combat transitions
- pause/unpause
- level load
Result: pass (music stable)
Not applicable is a valid regression result
Patch notes referenced a Dialogue Volume slider.
On this build:
- slider not present
Result:
STEA-103-AVOL → not applicable, with evidence
This avoids false assumptions about platform parity.
Key takeaway: regression testing in game QA
Regression testing is not full re-testing.
It is:
- risk-based
- change-driven
- evidence-supported
A strong regression testing workflow:
- protects the golden path
- targets high-risk areas
- verifies results clearly
This is what keeps builds stable after change.
Full article and case study
This DEV version focuses on the core workflow.
The full version includes:
- expanded regression testing structure
- deeper QA examples
- full case study and evidence
👉 Read the full updated version:

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