SmartBear released VisualTest, a new AI-powered automated regression testing tool that allows developers to easily catch visual defects and quickly confirm their website looks as designed, ensuring the best customer experience.
Automatically uncovering errors and highlighting inconsistencies using a robust comparison engine, VisualTest delivers component-level visibility alongside the automation processes for CI/CD, giving developers and testers visual accuracy and automation at scale. VisualTest also integrates with mobile and web application testing solution, BitBar, enabling teams to reduce context switching between visual, web, and real-device testing.
“Customer experience is critical for online businesses, especially now in a fiercely competitive environment,” said Joanna Schloss, Senior VP Product Marketing at SmartBear. “With frequent software updates common for SaaS and e-commerce companies, visual changes happen often and errors can frustrate users...It [VisualTest] is quick to deploy through self-service and easy to use, enabling developers to automate visual regression tests and correct problems before they get to the end user.”
With VisualTest, developers gain visibility into the design-and-build phase of the application with next-generation machine learning and AI engine tracking several types of visual changes. VisualTest ignores false positives while highlighting key differences, saving developers time and enhancing their applications. VisualTest essentially replicates the human eye for finding and catching visual errors that are not always detected through traditional functional or end-to-end testing. Using AI to run visual tests allows developers to focus only on important changes or differences. This aligns with the SmartBear goal of helping teams deploy with confidence by validating the quality of their UI in much less time.
Effective use of AI is critical to solve common testing challenges, especially those related to visual testing. Existing methods of visual testing are unreliable, time consuming, and cumbersome to maintain, and VisualTest fixes these problems through AI and other engineering innovations, significantly improving developer and tester productivity.
Compatible with Cypress, Selenium Python, and Selenium Java, VisualTest is easy to implement and use making it a great choice if you are just getting started. When you run a script, VisualTest automatically takes a screenshot, compares it to the previous version, and highlights crucial visual changes.
VisualTest is the latest in the company’s powerful and cost-effective suite of tools that give development teams unprecedented confidence in their software releases.
The Latest
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...