We've highlighted visual regression testing tools before and have observed their algorithms evolve from primitive pixel-level comparison to sophisticated pattern-matching and optical character recognition (OCR). Early visual regression tools generated many false positives and were only useful in later stages of development when the interface became stable. BackstopJS avoids this problem by configuring selectors and viewports to pinpoint visual tests to specific elements on the page. But machine learning has made it easier to detect and compare visual elements more accurately, even if they happen to have moved or contain dynamic content. These tools have become steadily more useful and are well-positioned to take advantage of the latest developments in AI and machine learning. Several commercial tools such as and now claim to use AI in their visual regression tests. One of our teams has been using Applitools Eyes extensively and have been happy with the results. Although visual regression tests are no substitute for well-written end-to-end functional tests, they're a valuable addition to the testing toolbox. We're moving them to adopt because they have become a safe default option as one element in a comprehensive UI test strategy.
Since we first mentioned visual regression testing tools in 2014, the use of the technique has spread and the tools landscape has evolved. BackstopJS remains an excellent choice with new features being added regularly, including support for running inside Docker containers. Loki was featured in our previous Radar. , and are SaaS solutions. Another notable mention is , an image diffing library. Although most teams use it indirectly as part of BackstopJS, some of our teams have been using it to analyze and compare images of web pages directly. In general, our experience shows that visual regression tools are less useful in the early stages when the interface goes through significant changes, but they certainly prove their worth as the product matures and the interface stabilizes.
