AI-AUGMENTED TEST AUTOMATION: LEVERAGING SELENIUM,CUCUMBER, AND CYPRESS FOR SCALABLE TESTING

Abstract

Thanks to improved efficiency, adaptability, and scalability, artificial intelligence is revolutionizing test automation in modern software development. Reliable test scripts, high maintenance costs, and inadequate adaptability to fit frequent user interface changes are among the challenges traditional test automation meets. Overcoming these limitations is made possible in part by self-repairing scripts, automated test case generation, and anomaly detection mixed with AI-driven solutions. Important instruments for commercial software testing, such as Selenium, Cucumber, and Cypress, offer special benefits as well. Selenium's cross-browser compatibility, Cucumber's behavior-driven development (BDD) approach, and Cypress's quick execution skills define basic elements of effective test automation systems. Human maintenance of these systems can thus be demanding and prone to mistakes. Artificial intelligence enhances these tools via forecasts of test failures, autonomous modification of test scripts, and reduction of duplicate test cases, increasing efficiency and dependability. Artificial intelligence makes major contributions to test automation in the following areas: AI-driven test scripts independently change to fit changes in the user interface, hence lowering the test failures resulting from small changes. Artificial intelligence looks over past data to create best test cases, hence improving test coverage and efficiency.AI-driven analytics for anomaly detection expose unusual behavior in application performance, therefore enabling early identification of likely development cycle difficulties. AI-driven test automation offers improved accuracy and faster delivery in fields including pharmaceutical benefit management (PBM) and healthcare, where regulatory conformity and software reliability are vital. Combining artificial intelligence with Selenium, Cucumber, and Cypress helps companies to streamline deployment schedules, maximize test dependability, and simplify testing processes. AI is improving rather than replacing existing testing technologies to create more intelligent, self-sustaining test automation systems. AI-enhanced testing becomes a transforming solution for attaining scalable, strong, and intelligent test automation as companies strive for improved software quality and accelerated releases.