Learn how Xray Enterprise keeps QA teams audit-ready with automated traceability, real-time test evidence, and version control.
Simplify QA governance and strategy with Xray. Centralize tests in Jira, improve traceability, and align QA with business goals and compliance.
Discover how AI, automation, and DevOps are reshaping QA in 2025, and why testers remain essential in a fast-changing software landscape
Discover how QA teams can leverage AI assistants to enhance test coverage, accelerate testing cycles, and improve defect detection - while navigating integration challenges and maintaining human oversight.
This article explores how a collaborative approach, supported by Xray’s test management capabilities in Jira, helps QA, development, and product teams align on automation priorities. Learn how to leverage traceability, reporting, and cross-functional insights to focus your automation efforts where they matter most.
Is your test automation strategy keeping up with the pace of modern development? Without the right tools, automation can become a bottleneck instead of an advantage. Xray Enterprise helps you integrate seamlessly with CI/CD pipelines, unify test management, and improve traceability - all while scaling effortlessly.
Test coverage is a key metric for assessing whether your test cases thoroughly validate an application’s functionality and requirements. Without a structured approach, teams risk missing critical scenarios and leaving defects undetected. Learn how Xray can help you eliminate manual tracking inefficiencies, improve visibility, and ensure every requirement is tested.
Managing test cases across multiple releases is a challenge for QA teams. Test Case Versioning changes the game by allowing teams to create, manage, and assign multiple test case versions. Learn how this feature helps QA teams streamline workflows and improve test execution reliability.
Software quality has evolved over time. Initially, the focus was on finding and resolving defects prior to a product launch. As technology advanced, the emphasis shifted towards maintaining quality ac
Discover how AI and shift-left testing streamline QA processes, ensuring high-quality software delivery while maintaining speed and efficiency.
With AI, testers can identify potential problems earlier, streamline planning, and enhance test coverage, all while improving resource management. While the transition brings its own challenges, such as data quality and skill adaptation, AI's benefits are vast. Learn about it here.
CI/CD pipelines are essential for fast and reliable software releases, but they come with challenges like team misalignment, flaky tests, and version control conflicts. This article explores these obstacles and offers solutions, such as optimizing testing, improving debugging, and enhancing security checks.
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