Software Quality is no longer measured solely by functionality, performance, and security, but also by the overall user experience (UX). Poor user experiences are known to cause businesses to lose up to 35% of their revenue. Visual testing is a software testing technique that ensures applications or websites meet expected to design and usability standards. This paper highlights the importance of visual testing in software development and its application in various industries, such as healthcare, e-commerce, gaming, and software development. We also discuss the challenges faced in manual visual testing and the need for automation to increase efficiency, accuracy, and scalability. Finally, we provide recommendations for incorporating visual testing into Agile development practices and creating a comprehensive testing strategy.
Quality engineering is an essential aspect of software development. Traditional testing techniques, such as functional testing, may not be enough to catch all issues, especially those related to the user interface (UI). The user experience (UX) is now considered a critical component of software quality, and businesses cannot afford to ignore it. Visual testing is a technique that ensures that the UI of an application or website meets the expected design and usability standards and that the UX is consistent across different devices, browsers, and platforms. This paper examines the importance of visual testing in software quality engineering and its application in various industries.
Visual testing is essential to ensuring that the UI of an application or website meets the expected design and usability standards. Any visual defects or inconsistencies can impact the user experience and lead to user frustration, reduced productivity, or even abandonment of the application. Traditional functional testing techniques may not catch all visual defects or layout issues, such as misaligned elements, broken images, or incorrect font sizes or colors. By detecting visual issues as early as possible in the development cycle, you can reduce the risk of having to make costly fixes later on, when the application is closer to release or even already in the hands of users.
Visual testing is a software testing technique that involves taking screenshots of the UI and comparing them to a set of baseline images to detect any visual differences or defects. This technique can be performed manually or using automated testing tools. Visual testing can also help you to ensure that the UI is consistent across different browsers, devices, and platforms, which is particularly important in today's multi-device, multi-platform environment. Visual testing is therefore an important part of a comprehensive testing strategy that can help you to improve the quality of your applications, enhance the user experience, and reduce the risk of user frustration or abandonment.
Visual testing is particularly important in industries where the UI is a critical component of the product or service. For example, in the healthcare industry, the UI of medical devices and software is essential to ensuring patient safety and accurate diagnosis. In the e-commerce industry, the UI of a website or mobile app is a key factor in providing a positive user experience and driving sales. In the gaming/streaming industry, the UI plays a crucial role in providing an immersive and enjoyable user experience.
Visual testing helps ensure that the UI is visually consistent, responsive, and engaging. In the automotive industry, the UI of a vehicle's dashboard and infotainment system is important to providing a safe and enjoyable driving experience. In the marketing/ad revenue industry, visual testing can help ensure that ads are displayed correctly and that they meet the expected design and branding standards. When websites are localized for a global presence, the UI may include text in different languages, as well as other changes to the layout, colors, and other visual elements to accommodate different cultural preferences.
Manual visual testing can be a time-consuming and error-prone process. It requires testers to inspect the UI for any defects or inconsistencies, which can be subjective and prone to human error. Testers may miss defects or inconsistencies due to fatigue, distractions, or other factors, leading to quality issues and delays in the testing process. Additionally, manual testing can be time-constrained when tests need to be repeated across multiple devices, browsers, or locales. Different testers may have different interpretations of what constitutes a defect or inconsistency in the UI, leading to inconsistent test results and making it difficult to establish a clear baseline for the expected appearance of the UI. As the application grows in size and complexity, manual testing can become more challenging and slow churning, leading to delays in the software delivery timeline.
Automated visual testing can help reduce the challenges associated with manual visual testing. Automated testing tools can take and compare screenshots, identify visual differences, log and report defects, and repeat tests as often as needed without additional manual effort. Automated visual testing can detect even the smallest visual differences between two images, which may not be noticeable to the human eye. Automation can also save time, increase efficiency, and improve
The adoption of visual testing in agile methodologies is crucial for ensuring that the user experience is consistent across devices and browsers. While visual testing is often associated with regression testing, it should also be included in story/epic sizing in sprints/releases, with attributes of the visual elements identified for coverage, such as layout, color, and typography.
Additionally, visual testing should be included in feature tests of the automation test suite and issues tracked with unique identifiers for clear issue traceability and analysis. Visual tests embedded with functional validations should be flagged with business priority rather than functional severity to ensure that functional tests pass while identifying observed visual issues. Furthermore, visual testing can lay the initial foundation for accessibility tests in the testing strategy, as visual cues are part of the accessibility validation process.
The areas of focus for visual tests must include colors, content/layout (hidden components, incorrect overlays, resizing effects, zero-pixel iframe, and iframe interactions), and dynamic data (smart lists and signal strengths for mobile).
However, there are challenges with automated visual testing, such as the time-consuming process of test creation for complex UI elements, cross-browser compatibility issues, which may result in false positives or negatives, and increased test maintenance requirements, particularly when there are frequent updates to the UI or the underlying code, requiring updates to baseline images.
Katalon condenses multiple asserts of home-grown automation solutions into three purpose-based modes: pixel, layout, and content comparisons. Additionally, Katalon applies AI for practical purposes such as image zoning, text comparisons, and the ability to ignore specific areas/zones within the images, which act as an efficiency booster and not a replacement for testers. Additional features such as batch updates for baselined images provide additional flexibility for temporary or permanent evaluation criteria, placing testers in charge with minimal overhead.
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Katalon also adopts a keyword approach for easy inclusion of visual testing within the automated functional tests, supporting browsers and mobile verifications with adequate failure handling included, thereby providing seamless adoption into existing tasks with minimal interruptions during functional validations. Furthermore, Katalon provides element, area, or page-level validation options for browsers and mobile devices, for even greater flexibility and a seamless adoption into the applied testing strategy. Finally, Katalon offers full control of pixel sensitivity when using pixel comparison, providing dynamic adoption for high testing agility, particularly for UI-focused revisions being released by the agile teams.
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Katalon visual testing provides leadership in driving value management by adding an additional dimension of quality evaluation while enabling the shift-left methodology for software delivery. It increases resource efficiency, delivery speed, and confidence in quality with a ‘create once and run everywhere, often’ approach. Additionally, baseline images created as test artifacts from release cycles can be referenced for observed user experiences for increased analytics, such as usability and accessibility, and other business initiatives.
Adopting visual testing in an agile environment can provide significant benefits to the software testing process. Visual testing tasks should be included as part of the story/epic sizing in sprints/release, and attributes of the visual elements should be identified for coverage across devices and browsers. Visual tests should be included within the feature tests of the automation test suite, and issues should be tracked with a unique tag/identifier.
Katalon can help streamline the testing process by condensing multiple 'asserts' into purpose-based modes, using applied AI for efficiency boosting, and offering options for element, area, or page level validation. Ultimately, the value of visual testing lies in its ability to add an additional dimension of quality to software delivery, increase resource efficiency and speed, increase confidence in software releases, and provide analytics for usability and accessibility. By incorporating visual testing into your testing strategy, software development teams can improve the overall quality of their products and enhance the user experience for their customers.