(Newswire.net — March 9, 2020) —
Software development for sites and applications designed for customer input and interaction is highly reliant on thorough quality assurance and testing. Appropriate testing helps ensure that functionality fits in with smooth user interface (UI) operation. The most common form of testing is visual, which is intended to examine how programs function on different devices, browsers, and operating systems. Visual testing has usually been done manually in order to mimic actual user behaviors. Manual testing has been used to detect visual display errors by depending on a human tester’s actual observations. There have been some advanced developments recently in automated testing systems that function as well or better than manual testing for UI errors. In this article, NearShore Technology looks at how these new tools assist developers in providing the best quality assurance possible.
Visual testing goes beyond verifying that desired elements are displayed to check for the proper layout and appearance of every element in all expected UI displays, including size, shape, and orientation. Testing also should verify correct fonts, colors, and image displays in expected UI layouts. Automated testing using machine learning methods differs mainly from human visual testing in how the testing software can “visualize” and interpret pixel layouts. While human vision can quickly see if a display looks correct or not, automated testing software can anticipate how even subtle shifts in layout from changes or operation on different devices or browsers can greatly affect display and functionality.
Automated visual testing tools should be integrated into the entire development process so that programmers, testers, and product owners can work together to create an automation strategy that will promote the integration of corrections as early as possible, saving redundant work and wasted time.
Automated testing tools must inspect an application’s UI layout in the same cognitive manner as human users do. All integrated images should be examined as a whole to determine that every element is visible and properly configured. Automated testing identifies errors and also categorizes them as being related to content, appearance, or layout. The testing software should also be powerful enough to make systemic error corrections once in order to correct similar errors on other pages or screens.
These types of testing programs must be able to manage a large amount of image data, and a low storage footprint is essential to efficient and accurate testing. Automated testing requires storage of proper baseline images and actual images as displayed. Any errors and changes are also preserved and stored. The testing system must, therefore, use very efficient image compression to maintain all the needed images within a reasonable storage footprint. Automated testing also should manage baseline image expectations across all expected display environments. Image displays vary significantly between different devices and browsers, and automated testing should be able to track baseline image changes among the variety of UI environments that are tested. Many new automated testing tools automatically take screenshots of UI interfaces across various display configurations, which allows human testers to compare page layouts side-by-side both before and after errors are corrected.
About NearShore Technology
NearShore Technology is a US firm headquartered in Atlanta with offices throughout North America. The company focuses on meeting all the technology needs of its clients. NearShore partners with technology officers and leaders to provide effective and timely solutions that fit each customer’s unique needs. NearShore uses a family-based approach to provide superior IT, Medtech, Fintech, and related services to our customers and partners throughout North America.