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Test cases
Wearable test cases, for the workout that never made it back
Twenty eight cases covering data recorded while the phone is out of range, duplicate records on resync, interrupted syncs, full on device buffers, conflict resolution, clock drift, standalone mode, health permission revocation, battery budgets, unworn device readings and totals reconciling across all three surfaces.
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28 worked examples
Pair the wearable with the phone application
TypeFunctionalPriorityHigh- Test data
- A first time pairing followed by the initial data sync
- Expected result
- Pairing completes, the account is linked, and existing data on the phone appears on the device without requiring a manual trigger.
Record data while the phone is out of range
TypeStatePriorityHigh- Test data
- Leave the phone behind, record an activity on the watch, then return
- Expected result
- Everything recorded is buffered on the device and synced on reconnection. Losing it is the defect this whole set exists to prevent.
Sync a long offline period without duplication
TypeBoundaryPriorityHigh- Test data
- Several days of readings accumulated offline, then reconnected
- Expected result
- Every record arrives exactly once. Sync is retried on unreliable transports, so records need stable identifiers to survive redelivery.
Resume an interrupted sync
TypeStatePriorityHigh- Test data
- Move out of range partway through a large sync, then return
- Expected result
- Resumes from where it stopped rather than restarting, and no partially transferred record is committed as complete.
Handle a full on device buffer
TypeBoundaryPriorityHigh- Test data
- Record beyond the device storage allocation while disconnected
- Expected result
- Documented behaviour applied and the user is warned before data is lost, rather than the oldest readings being discarded silently.
Resolve a conflict between device and phone
TypeBoundaryPriorityHigh- Test data
- The same activity edited on the phone and on the watch while disconnected
- Expected result
- Documented conflict rule applied consistently, and the user is asked when the resolution would discard something they entered.
Order records correctly across a timezone change
TypeBoundaryPriorityHigh- Test data
- Records made either side of a timezone change and a daylight saving transition
- Expected result
- Chronological order is correct, each record keeps the timezone it was recorded in, and a day boundary is evaluated consistently on both devices.
Handle the watch clock drifting from the phone
TypeBoundaryPriorityHigh- Test data
- A device clock offset by several minutes from the phone at the time of recording
- Expected result
- Timestamps are reconciled or the offset is recorded, so a reading does not appear to occur before the activity that produced it.
Operate in standalone mode without the phone
TypeFunctionalPriorityHigh- Test data
- The phone powered off, with the watch on its own network connection
- Expected result
- Documented standalone features work independently, and anything requiring the phone states so rather than failing with a generic error.
Handle the companion app being uninstalled
TypeNegativePriorityHigh- Test data
- Uninstall the phone application while the watch app is installed
- Expected result
- Watch app reports the disconnection clearly and buffered data is preserved or exported rather than discarded on the next launch.
Unpair and re-pair without duplicating history
TypeStatePriorityHigh- Test data
- Unpair, re-pair, then compare the history on both devices
- Expected result
- Records are matched rather than re-imported, so a re-pair does not double every historical entry.
Pair with a second phone or a replacement device
TypeStatePriorityMedium- Test data
- Move the wearable to a new phone signed into the same account
- Expected result
- History follows the account, the previous pairing is cleanly released, and data is not stranded on the old device.
Request health permissions correctly
TypeSecurityPriorityHigh- Test data
- Grant some health data types and deny others
- Expected result
- Only the granted types are read, denied types degrade the feature with an explanation, and the app does not infer denied data from other sources.
Detect a health permission revoked later
TypeStatePriorityHigh- Test data
- Revoke a previously granted health permission in system settings
- Expected result
- Detected on next use rather than assumed, reading stops immediately, and already synced data is handled per the documented retention rule.
Protect health data at rest and in transit
TypeSecurityPriorityHigh- Test data
- Inspect on device storage, the sync payload and any logs
- Expected result
- Encrypted in transit and at rest, absent from logs and analytics, and not transmitted to any third party without explicit consent.
Keep battery consumption within budget
TypePerformancePriorityHigh- Test data
- Continuous recording for a full day with the app active
- Expected result
- Drain stays inside the stated budget. An app that flattens the battery by mid afternoon stops recording, which is data loss by another route.
Reduce activity in low power mode
TypeStatePriorityHigh- Test data
- Enter the device low power state during an active recording
- Expected result
- Sampling reduces rather than stopping, the user is told what changed, and the recording is not silently abandoned.
Continue recording when the screen is off
TypeStatePriorityHigh- Test data
- Start a recording, lower the wrist, and leave the screen off for an extended period
- Expected result
- Recording continues through the background mechanism intended for it rather than pausing whenever the display sleeps.
Handle the app being killed mid recording
TypeStatePriorityHigh- Test data
- Force stop the watch app during an active recording
- Expected result
- Data captured up to that point survives and the partial session is recoverable rather than discarded as incomplete.
Update a complication or watch face element
TypeFunctionalPriorityMedium- Test data
- A complication showing a live figure across a day, including after a sync
- Expected result
- Updates within the platform budget, never shows a stale figure without indicating its age, and degrades to a placeholder rather than a blank.
Deliver notifications without duplicating the phone
TypeFunctionalPriorityMedium- Test data
- A notification arriving while both devices are active, and while only the watch is worn
- Expected result
- Delivered to one device according to platform convention, and dismissing it on one clears it on the other.
Complete a task on the smallest supported screen
TypeCompatibilityPriorityHigh- Test data
- Every core journey on the smallest supported device size at the largest text setting
- Expected result
- No control is clipped or unreachable, scrolling reaches every action, and no journey depends on text that cannot be read at that size.
Handle input methods available on the device
TypeCompatibilityPriorityMedium- Test data
- Touch, crown or bezel rotation, voice input and a paired keyboard where supported
- Expected result
- Each supported method works for every input, and no task requires typing where the device provides no practical way to type.
Work correctly with wet hands or a glove
TypeCompatibilityPriorityMedium- Test data
- Touch input with water on the screen and with the platform water lock engaged
- Expected result
- Documented behaviour applies, accidental input is rejected while locked, and an active recording is not disrupted by the lock state.
Detect that the device is not being worn
TypeStatePriorityMedium- Test data
- Remove the device during an active recording
- Expected result
- Readings from an unworn device are marked or discarded rather than recorded as genuine measurements, which would corrupt the day totals.
Migrate on device data across an app update
TypeCompatibilityPriorityHigh- Test data
- Unsynced buffered data present when the watch app is updated
- Expected result
- Buffer survives the update and syncs afterwards, rather than being discarded because the storage format changed.
Reconcile totals between watch, phone and server
TypeStatePriorityHigh- Test data
- A full day of activity compared across all three surfaces
- Expected result
- All three agree. A daily total that differs between the watch and the phone is the most visible and most reported wearable defect.
Operate the watch app with accessibility features enabled
TypeAccessibilityPriorityMedium- Test data
- Screen reader enabled at the largest text size with reduced motion
- Expected result
- Every control is labelled and reachable, values are announced with their units, and haptic feedback is not the only signal for an outcome.
What goes in each field
ID
RequiredStable identifier, prefixed by module.
Test case
RequiredWhat is being verified, in one line.
Type
Functional, negative, boundary, security, state, performance, accessibility or compatibility. Use it to check coverage is spread rather than clustered on the happy path.
Priority
Risk based. Anything that loses data recorded on the device, duplicates it on sync, or drains the battery to the point the device stops recording is High. Small screen usability issues are Medium unless they block a task.
Test data
The specific values, including the invalid and boundary ones.
Expected result
RequiredThe precise observable outcome, including message text where the wording itself is the requirement.
Leave the phone at home
Syncing while both devices sit on a desk proves nothing. These four conditions are where wearable data is lost or doubled.
Record with the phone out of range
Then come back and check every record arrived. Losing a workout or a health reading is the one defect users never forgive, and it is invisible when testing side by side.
Interrupt the sync halfway
Walk out of range mid transfer. Sync retries over unreliable transports, so records need stable identifiers or the second attempt duplicates everything already sent.
Wear it for a full day
Battery is a correctness concern here, not a performance one. An app that flattens the battery by mid afternoon stops recording, which is data loss by another route.
Compare all three totals
Watch, phone and server for the same day. A daily figure that differs between devices is the most visible and most reported wearable defect there is.
Why wearable defects lose data
A wearable is a device that is routinely disconnected from the thing it syncs to, which makes it a distributed system rather than an accessory. Everything recorded while the phone is elsewhere lives only on the watch until it is transferred, and the transfer happens over a transport that drops constantly. That produces the two defects worth building this set around: data that never arrives, and data that arrives twice because the sync retried. Both need stable record identifiers and a resumable transfer, and neither shows up when both devices are sitting on the same desk.
Buffering has a limit and that limit needs a defined behaviour. A device recording for days without a phone will fill its allocation, and silently discarding the oldest readings is the worst available option because the user has no idea it happened. Conflict resolution belongs in the same category: the same activity edited on both devices while disconnected has to resolve by a documented rule, and the user should be asked whenever resolving it would throw away something they typed.
Time is unusually hard here because there are two clocks. A watch that has drifted from the phone will produce timestamps that place a reading before the activity that generated it, and a timezone change mid day will reorder records or move them across a day boundary so the daily totals disagree. Recording the timezone with each entry and reconciling the offset at sync are both cheap, and both are commonly skipped.
Finally, battery is a correctness concern on a wearable rather than a performance nicety. An app that drains the battery by mid afternoon stops recording for the rest of the day, which the user experiences as missing data rather than as poor battery life. The related cases are the low power state, where sampling should reduce rather than stop, and the screen being off, where recording must continue through the intended background mechanism rather than pausing every time the wrist drops.
Suggest an improvementTesting a wearable or companion app?
QAble tests wearable applications on real devices, including offline buffering and resync, conflict resolution, health data handling and battery behaviour over a full day.
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