Compatibility testing driven by who actually uses your product
You cannot test every browser, device and operating system, and you should not try. We build a support matrix from your real audience and your risks, test it properly, and state clearly what falls outside it.
Overview
What it is. Compatibility testing checks that a product behaves correctly and consistently across the browsers, devices, operating systems, screen sizes, networks and software combinations its users actually have.
Who it is for. Teams with consumer-facing web or mobile products, games, and software used on varied hardware and across regions with different device mixes.
Why it matters
The problem it addresses. A product can pass every test on the machines of its developers and still fail for a large share of its audience: a layout that breaks on one browser version, a feature that crashes on a particular phone, a flow that stalls on a slow network.
When it matters most. Before launch, when adding a new platform or major OS version, when analytics show a shift in the audience's devices, and when support tickets cluster around specific configurations.
What happens without it. Problems are reported by users on configurations the team never saw, review ratings drop, and store visibility can suffer for device-specific failures.
What we test
Support-matrix definition from analytics, market data and risk
Browser and browser-version coverage for web products, informed by feature support data
Mobile device, OS version, screen size and form-factor coverage, including rotation and foldables
Network conditions
slow, interrupted and changing connections
Operating-system and software co-existence for desktop and embedded contexts
Visual and functional comparison across configurations
Reporting of untested combinations as a stated risk
How UpDoer approaches Compatibility Testing
Understand
Requirements, tickets, code diffs and product context.
We gather your analytics, support tickets, target markets and platform commitments to see what users actually run.
Risk Mapping
Where a failure would cost the most.
Browsers, devices and operating systems are ranked by audience share and by the cost of failure on each, producing a tiered support matrix.
Test Strategy
Coverage chosen, test cases drafted.
We decide which tier gets full testing, which gets smoke coverage and which is out of scope, and agree where real devices are essential.
Execute
Manual and automated testing runs.
Functional and visual checks run across the matrix, using real devices where behaviour depends on hardware and other setups where it does not.
AI-Assisted Quality Engineering
Failures classified, release risk scored.
AI compares screens across configurations, clusters failures by device, OS or browser, and highlights differences that a person should look at first.
Human Verification
A QA engineer checks every flagged result.
A QA engineer judges which differences matter to users, confirms device-specific defects on real hardware, and assesses touch, sensors and interruptions.
Report & Improve
The verified quality signal, then better coverage.
Reports show results per tier, list untested combinations and their risk, and recommend changes to the matrix as the audience shifts.
Compatibility: testing what your users actually run
01
Where it breaks
Layout breaks on one browserCrash on one phone modelStalls on slow networks02
Test workflow
AudienceMatrixTestCompare03
AI assists
Compare screens across setupsGroup failures by deviceSuggest matrix changes04
Humans decide
Decide the support matrixCheck real-hardware behaviour05
Release signal
Results by tierUntested list shownRisk accepted knowingly
Illustrative workflow. Not a client result or a measured outcome.
Compatibility dimensions
A dash means no AI step is described for that area.
| Dimension | Examples of what is varied | What we validate | AI assistance | Human validation |
|---|---|---|---|---|
| Browsers | Chrome, Edge, Firefox, Safari; current and previous versions | Layout, features, scripts, forms | — | Judges user impact of differences |
| Mobile devices | Phone and tablet models, OS versions | Install, launch, flows, performance | Groups failures by device | Confirms on real hardware |
| Screen and form factor | Small phones, tablets, foldables, orientations | Adaptive layouts, rotation, fold transitions | — | Reviews usability at each size |
| Networks | Slow, intermittent, switching networks | Loading, retries, offline messages | Spots network-specific failures | Judges acceptable behaviour |
| Operating systems | Windows and macOS versions, mobile OS updates | Install, permissions, co-existence | Notes OS-specific patterns | Assesses risk of untested versions |
| Software co-existence | Other apps, extensions, security software | Conflicts and interoperability | — | Judges whether to support or document |
Dimension: Browsers
- EXAMPLES OF WHAT IS VARIED
- Chrome, Edge, Firefox, Safari; current and previous versions
- WHAT WE VALIDATE
- Layout, features, scripts, forms
- AI ASSISTANCE
- —
- HUMAN VALIDATION
- Judges user impact of differences
Dimension: Mobile devices
- EXAMPLES OF WHAT IS VARIED
- Phone and tablet models, OS versions
- WHAT WE VALIDATE
- Install, launch, flows, performance
- AI ASSISTANCE
- Groups failures by device
- HUMAN VALIDATION
- Confirms on real hardware
Dimension: Screen and form factor
- EXAMPLES OF WHAT IS VARIED
- Small phones, tablets, foldables, orientations
- WHAT WE VALIDATE
- Adaptive layouts, rotation, fold transitions
- AI ASSISTANCE
- —
- HUMAN VALIDATION
- Reviews usability at each size
Dimension: Networks
- EXAMPLES OF WHAT IS VARIED
- Slow, intermittent, switching networks
- WHAT WE VALIDATE
- Loading, retries, offline messages
- AI ASSISTANCE
- Spots network-specific failures
- HUMAN VALIDATION
- Judges acceptable behaviour
Dimension: Operating systems
- EXAMPLES OF WHAT IS VARIED
- Windows and macOS versions, mobile OS updates
- WHAT WE VALIDATE
- Install, permissions, co-existence
- AI ASSISTANCE
- Notes OS-specific patterns
- HUMAN VALIDATION
- Assesses risk of untested versions
Dimension: Software co-existence
- EXAMPLES OF WHAT IS VARIED
- Other apps, extensions, security software
- WHAT WE VALIDATE
- Conflicts and interoperability
- AI ASSISTANCE
- —
- HUMAN VALIDATION
- Judges whether to support or document
Where AI helps
- Clustering failures by device model, OS version or browser to show whether a defect is general or isolated.
- Spotting repeated failures that appear only on certain network conditions.
How we use AI: AI can accelerate test design, analysis and repetitive QA work, but important outputs remain subject to human review and validation. It informs the release decision; it does not make it.
Where humans matter
- Deciding the support matrix and accepting the risk of what is outside it.
- Judging whether a rendering or layout difference matters to a real user.
- Testing behaviour that depends on hardware: touch, sensors, camera, interruptions, battery and thermal conditions.
- Confirming that a device-specific defect is the product's fault and not the test setup's.
- Reporting coverage gaps plainly.
Tools we build with
- Automation
- SeleniumPlaywrightAppiumKatalonTestComplete
- API & Performance
- PostmanSoapUISwaggerApache JMeter
- CI/CD & Reporting
- JenkinsTeamCityAllureMaven
Frequently asked questions
How do you choose which browsers and devices to cover?
From your analytics, target markets and business risk, not from a generic list. The result is a tiered support matrix you can review and change.
What happens to configurations outside the matrix?
They are listed as untested, with the risk stated, so the decision to accept it is made knowingly.
Can AI replace testing on many devices?
No. AI helps compare and group results across configurations. Real-device behaviour still needs real devices and a person to judge it.