{"id":19538,"date":"2026-07-24T17:20:44","date_gmt":"2026-07-24T17:20:44","guid":{"rendered":"http:\/\/localhost\/webcasata\/surbhi\/qyrus\/?p=19538"},"modified":"2026-07-24T17:29:59","modified_gmt":"2026-07-24T17:29:59","slug":"v6-20-0-july-2026-release","status":"publish","type":"post","link":"https:\/\/symmetricsolutionz.co.in\/qyrus\/v6-20-0-july-2026-release\/","title":{"rendered":"V6.20.0 (July 2026 Release)"},"content":{"rendered":"\t\t
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Welcome to the July release!\u00a0<\/span>\u00a0<\/span><\/p>

This month, our engineering teams focused on advancing our AI capabilities, streamlining enterprise collaboration, and fortifying foundational performance across every corner of the platform.<\/span>\u00a0<\/span><\/p>

As testing pipelines scale and applications become more dynamic, efficiency and visibility are paramount. In\u00a0<\/span>Web Testing<\/span><\/b>, we are putting you in complete control of your AI workflows with a new Two-Stage Test Generation pipeline that previews scenarios before building code\u2014slashing latency and saving tokens.\u00a0We\u2019re\u00a0also embedding continuous quality assurance directly into your suites with the new AI-powered LLM Evaluator Service, while solidifying modular architecture with permanent Function Step Reference Linking and centralized integration security.<\/span>\u00a0<\/span><\/p>

In\u00a0<\/span>API Testing<\/span><\/b>, we are bridging the gap between quality engineering and generative AI by introducing a dedicated RAG Evaluation Test Type. This feature empowers you to validate LLM faithfulness, relevance, and citation precision natively alongside your standard REST suites. We have also overhauled large-scale workspace management with high-performance asynchronous cloning jobs to ensure smooth, uninterrupted UI performance.<\/span>\u00a0<\/span><\/p>

Our cross-platform execution engines have received major usability upgrades as well.\u00a0<\/span>Desktop Testing<\/span><\/b>\u00a0now automatically detects and flags parameterized scripts, while\u00a0<\/span>Test Orchestration<\/span><\/b>\u00a0gains comprehensive loop\u00a0rendering\u00a0for desktop workflows. Collaboration and resource management are smoother than ever:\u00a0<\/span>Device Farm<\/span><\/b>\u00a0introduces team-based hardware filtering and hardened AI session stability, and\u00a0<\/span>Test Orchestration<\/span><\/b>\u00a0brings you one-click Report Deep Linking, integrated Jira defect creation, and real-time device and browser availability indicators right in your run configurations.<\/span>\u00a0<\/span><\/p>

Let\u2019s\u00a0dive into the full breakdown of everything new across the platform this July!<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Web Testing <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/path><\/svg><\/span>\n\t\t\t<\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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Smart Optimization: Two-Stage Test Generation!<\/span><\/span>\u00a0<\/span><\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
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The Challenge:<\/span><\/b>\u00a0<\/span>\u00a0<\/span><\/p>

Generating comprehensive web automation scripts using AI is incredibly powerful, but parsing full test steps, localizing elements, and compiling underlying logic requires high processing power and time. Previously, Test Generator v2\u00a0operated as\u00a0a single, continuous pipeline. The engine would\u00a0immediately\u00a0build the full, granular steps for every single scenario it conceived. If the\u00a0initial\u00a0high-level testing path\u00a0wasn’t\u00a0exactly what you needed, tokens and execution time were wasted creating detailed code for a script you\u00a0ultimately discarded.<\/span>\u00a0<\/span><\/p>

The Fix:<\/span><\/b>\u00a0<\/span>\u00a0<\/span><\/p>

We have re-architected\u00a0<\/span>Test Generator v2<\/span><\/b>\u00a0into a high-efficiency, two-stage generation pipeline. In the first stage, the AI quickly drafts a high-level preview of the contextual test scenarios for your review. Once you scan the overview and select the specific paths you want, the engine moves to the second stage\u2014utilizing\u00a0historical context and deep memory\u00a0<\/span>only<\/span><\/i>\u00a0to build the detailed execution steps for your chosen scenarios.<\/span>\u00a0<\/span><\/p>

How will it help?<\/span><\/b>\u00a0<\/span>\u00a0<\/span><\/p>

This intelligent layout shift gives you total control over the AI engine, drastically cutting down on test creation overhead.<\/span>\u00a0<\/span><\/p>