Using test frameworks, engineers write special scripts, simulating user interaction with a web app. The main purpose of it is finding bugs in the software. Special scripts are automatic. Thus, human intervention is minimized, the accuracy and speed of checks are much higher.
For big and complex projects including web apps with strictly regulated SLAs or with high-priority and frequently used features or a large number of users (who care about the interface response time and transaction speed), web test automation is the only option to achieve the optimal level of test efficiency and coverage.
Automated regression testing allows to quickly run simple scripts and test various changes to get rapid feedback. To check the continuous compatibility between the web app and the specified versions of operating systems, browsers and devices as well as to test the app performance under the influence of stressful conditions or a high level of load is possible only with web automated testing.
If you need to execute test suites containing 1000+ tests, but your budget does not allow you to get unlimited infrastructure or, in contrast, you pay a fixed upper limit for the infrastructure that is not used at full capacity, Zebrunner Selenium Grid is at your service. It helps to execute up to 1k tests in parallel in less than 15 minutes (in its own Cloud or On-premise machines). Run tests quickly, handle bugs faster and release into the market on time. Payment is made only for the time used.
Track the performance of QA engineers and their success in finding defects, plan timelines for releases, monitor testing progress and application quality in a few clicks with Zebrunner Testing Platform. QA managers can build flexible dashboards and customize them by adding specific widgets with metrics. It allows them to control all QA processes quickly and visibly, freeing up time for management activities.
Quickly check the failure category and find out the issue with Zebrunner Testing Platform using AI/ML automatic classification. Each time a test fails, AI/ML assigns a certain failure category depending on the stack trace. To enhance the accuracy of the results up to 100%, you can train the system by accepting or modifying the results of the AI/ML. You can also discover the causes of failure with rich test artifacts (screenshots, videos, test logs).
Ensures that every function of a web app is working according to the predefined requirements and the customer or end-user is satisfied. It checks the proper functioning of the links, navigation, business logic and the functions performed by the AUT.
Checks whether new features, improvements and fixed defects affect the existing functionality of the web app and whether old defects recur. It covers lots of functionality (customer workflows, all the functions and back-end processes).
.svg)
Tests the web application's ability to resist and effectively recover from potential failures due to software errors, hardware failures, or communication problems (network failure, power failure, etc.).
.svg)
Tests the speed, responsiveness, scalability and stability of the web application under various stress conditions or load level. Performance testing ensures that the app can withstand long periods of activity or peak user loads.
.svg)
Evaluates the behavior of the web application in different browsers (e.g. Chrome, Firefox, Safari, Opera, Edge), across various operating systems and on multiple devices (desktop, mobile, or both if the software has desktop and mobile versions), with different screen resolutions.
Represents a specific process of implementing automated checks within the software development/delivery pipeline to get feedback on potential business risks related to the software release candidate as soon as possible. It covers many types of testing, from simple unit tests to complex web accessibility checks.
