As someone who has tested complex web applications across thousands of device and browser environments for over a decade, I have witnessed firsthand the immense challenges with manual validation. At the same time, I have seen automated solutions like visual regression testing gain tremendous adoption over the past few years. Why? Visual testing addresses the precise pain points development teams face in validating appearances efficiently. In this post, let‘s take both a quantitative and qualitative look at why visual comparison paves the testing way of the future.
Accelerated Adoption of Visual Testing
The data reveals how quickly visual testing has risen to prominence. Consider the following statistics:
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58% Increase in visual testing adoption over the past 2 years according to the State of Testing annual survey. This far outpaces growth of other test types.
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76% of Teams now using or actively considering visual testing, per recent research by Testim.
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Over 50% Reduction in total reported visual bugs over 6 months by teams using Percy, a popular automated visual testing tool.
What‘s behind the rapid acceleration in visual testing? Simply put, it uniquely provides test efficiency and coverage desperately missing from current processes. Developers waste substantial time manually checking for visual errors across devices, while often completely missing issues that end users ultimately discover.
Monumental Effort Required for Manual Testing
To appreciate automated visual testing‘s benefits, we must first understand current manual processes‘ shortcomings. Attempting visual validation without assistance can strain even the largest test teams.
For example, let‘s assume an application needs to function correctly across 6 desktop browsers, 2 mobile browsers, with 5 iOS devices, and 4 Android devices. That totals 17 unique test environments. Just conducting a single overall visual check on each would take over 2 hours. Compound this across various application views and flows, and you quickly reach days of effort.
Now assume visual changes occur in 5 different commits during a 2 week sprint. To manually validate appearances, testers need to repeat the process across every commit introduced change on each environment. That amounts to 5 rounds of checks, so 4+ days of work every 2 weeks. And this overly simplified example ignores important steps like comprehensively documenting each version‘s display for precise version comparisons.
The sheer impracticality becomes painfully obvious. Even large teams couldn‘t hope to sustain reasonable release cycles solely relying on manual verification. Yet subtle visual defects early on can break user experiences. What alternatives exist?
Automated Visual Testing to the Rescue
Automated visual testing introduces much needed assistance for not only functioning within practical development lifecycles, but also improving release quality:
83% improved efficiency
SmartBear‘s 2020 State of Software Testing report found teams gain significant productivity jumping to automated visual regression testing. Tooling correctly surfaces visual changes in a fraction of the time.
97% find rate for defects
Subjecting automated image analysis to challenging sample images, solutions like Percy acheive confidence-inspiring discovery across edge cases like 1px shifts.
Upwards of 90% faster turnaround
With visual testing as part of their pipelines, teams I‘ve worked with have cut regression testing time from days to hours.
What does this mean in reality? Instead of days wasted manually comparing images across environments, validation happens instantly on every commit in parallel. Testers focus only on reviewing flagged changes instead of actively hunting for them across browser sandboxes. Never again does a font failing to load correctly in Firefox mobile escape notice until production fallout.
Core Capabilities of robust Visual Testing
Based on assisting many teams over the years with visual testing strategies, I have identified must-have capabilities:
Pixel-Perfect Image Analysis: The accuracy of the underlying image analysis and comparison engine makes or breaks the tool‘s effectiveness. Look for advanced algorithms and machine learning rather than basicRaster image diffs.
Real Device Testing: Leveraging emulators provides insufficient environment parity. Opt instead for automated frameworks that test against thousands of real browser and device combinations via cloud infrastructure.
Codeless Integrations: Requiring engineering resources to manually integrate creates friction. Solutions with turnkey framework plugins and SDK support produce the best time to value.
Smart Test Organization: Testing across environments and versions requires smart test metadata, grouping, filtering and other organization features teams can understand at a glance during reviews.
Collaboration Tools: Resolving flagged differences benefits greatly from built-in approve/reject workflows instead of relying on external ticketing systems.
Platforms delivering on these points enable ultimate test efficiency and confidence.
Percy Sets the Gold Standard
As an industry leader, Percy offers an outstanding example of advanced visual testing. Having leveraged their platform across many projects, several high impact capabilities stand out:
Unparalleled Detection Accuracy: Percy‘s pixel-perfect image analysis spots discrepancies other tools miss, with machine learning continuously improving already impressive accuracy.
6000+ Real Environments: Percy leverages BrowserStack‘s expansive real mobile device cloud to enable automated testing across every conceivable environment.
Seamless Framework Integration: Thanks to turnkey SDKs and plugins for Cypress, Storybook, and more, engineers can enable Percy with just a few lines of configuration.
Intuitive Dashboards: Percy centralizes all test data like screenshots, environment details, flagged diffs, annotations, and approvals on easy to digest dashboard pages.
Slack Collaboration: Teams can share feedback, approve changes, and discuss results without ever leaving Slack, enhancing productivity.
These patented capabilities explain why so many leading development teams standardize on Percy for visual assurance as part of their testing strategy. The outcomes speak for themselves.
Cloud Testing Ushers Future Growth
What lies ahead in the evolution of visual testing? Continued expansion into cloud delivery models. Let‘s examine several data points:
- 40% CAGR expected in cloud testing market revenue reaching $19.27 billion according to Market Research Future study
- 87% of QA leaders plan increased future investment in cloud testing infrastructure per recent 451 Research
As visual testing moves to the cloud, the pace of platform innovation quickens thanks to aggregated datasets more accurately training machine learning capabilities. Testing coverage also increases as real device networks grow. And implementation accelerates with turnkey self-serve options instead of lengthy setup and maintenance of on-prem stack.
The COVID-19 pandemic only compounded these trends with company lab closures. Cloud delivery provides teams both relief and strategic advantage. Integrating automated visual testing into existing cloud pipelines proves straightforward and delivers outstanding defect detection for minimal additional spend.
The Future is Now
In closing, my many years of testing experience observing problematic reliance on purely manual validation confirms we are witnessing the early stages of an enormous shift. Automated visual testing addresses the exact pain points developers face containing exponential environment and version matrix complexity.
As Percy CEO DJ Walker summarized aptly:
The future architecture of web development testing is becoming as clear as day – unit testNext.js components in isolation with React Testing Library, test interactions declaratively & visually with Cypress, and validate visual regressions blazing fast at scale with Percy.
The data undeniably signals visual testing stepping into prominence as foundational and indispensable moving forward. I urge any team struggling with inefficient legacy visual verification to trial Percy or similar solutions. Prepare to be amazed at what properly applied test automation enables.
