Integrate performance testing into Agile with Xray for faster releases, better user experience, and full Jira traceability.
Understand how Xray’s Requirement Coverage brings real-time visibility to your testing efforts. By connecting test executions to Jira requirements, teams can automate traceability, reduce release risks, and ensure compliance in fast-paced environments. Learn how to set it up, avoid common pitfalls, and integrate coverage insights directly into your CI/CD workflows.
Too often, software testing metrics are reduced to pass/fail numbers or bug counts. But if you're only looking at those, you're missing the bigger picture. This article explores how QA metrics can be used strategically — not just to track performance, but to connect your team’s work directly to business outcomes. Learn which metrics matter most (like defect leakage and requirements coverage), how to use them to make better decisions, and how tools like Xray can support your strategy.
When choosing a test management tool for Jira, which one is best? Learn more about Xray vs Zephyr for Jira testing.
Manual test management can only take you so far. As software development accelerates, teams need scalable, automated strategies to stay ahead. In this article, you'll explore the shift from manual to automated test management.
Simplify QA governance and strategy with Xray. Centralize tests in Jira, improve traceability, and align QA with business goals and compliance.
From managing large datasets to integrating with CI/CD pipelines, QA teams face several roadblocks that can compromise test results and efficiency. In this article, we explore five common challenges in data-driven testing and provide practical solutions to help your team overcome them and scale smarter.
Test parameterization enables testers to execute the same test case with multiple input datasets, reducing redundancy and improving test efficiency. Instead of hardcoding values, testers define variables that are dynamically replaced during execution. Learn how to implement it in your testing strategy.
Data-driven testing separates test logic from data, allowing multiple input variations to be tested efficiently. Meanwhile, keyword-driven testing simplifies automation by defining reusable actions, making it accessible to non-technical testers. In this blog post, we compare both methodologies and show you which one you should choose.
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.
Automation metrics are more than just numbers - they offer valuable insights into test efficiency, defect detection, and overall software quality. In this guide, you'll find the key metrics that matter most for QA leads, from test coverage and execution time to flaky test rates and automation ROI.
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