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  • Re-usable test steps, where they synchronize and update themselves. Current saved scripts for SAP don't have re-usable steps for login for example, login would be re-used across the demo

  • Selenium grid on Premises, and replace lambda test

  • Microsoft co-pilot support, publish reports into co-pilot and enable access from co-pilot - this is important to show partnership and alignment with Microsoft

  • Testing of windows desktop applications (STC)

  • Testing of Native mobile Apps (Kina bank)

  • Generate tests from service now

  • Generate tests from BDD in Gherkin format

  • Re-usable test blocks (not a copy)

  • Performance testing

 

Feature

Focus

Perceived Value

Customer Reference

Re-usable test steps

Synchronize and update themselves, allowing re-use across different scripts

Reduced redundancy, streamlined test maintenance, increased efficiency

Selenium grid on Premises

Provide an on-premises alternative to cloud-based Selenium grids

Enhanced security, lower latency, compliance with internal policies

-

Microsoft co-pilot support

Publish reports into co-pilot and enable access from co-pilot, showing partnership with Microsoft

Improved collaboration, seamless report access, leveraging Microsoft ecosystem

-

Testing of Windows desktop applications

Support for testing Windows desktop applications (STC)

Comprehensive testing capabilities for desktop applications

STC

Testing of Native mobile Apps

Support for testing native mobile applications

Comprehensive mobile app testing, ensuring high app quality

Kina Bank

Generate tests from ServiceNow

Automatically generate tests based on ServiceNow workflows

Increased efficiency in test creation, integration with ServiceNow

-

Generate tests from BDD in Gherkin format

Support for generating tests from Behavior-Driven Development (BDD) in Gherkin format

Enhanced collaboration between technical and non-technical team members

-

Re-usable test blocks

Utilize re-usable test blocks without copying

Reduced test creation time, easier maintenance, consistency in test execution

-

Performance testing

Comprehensive performance testing capabilities

Ensure application performance under load, identify bottlenecks

-

Testing for AI Chatbots

  • verify that the chatbot is responding with:

  • good answers,

  • teachning and not answering

  • not sharing confidencial information

  • company policies for <x> compliance

RC EDU Chatbot (teaching assistant)

Generative AI features

  • Natural-language-driven test authoring

  • Automatically generate a set of test cases based on a natural language description (written or verbal) of a use case or a requirement

  • Interactive AI-powered assistant

  • Interact with the tool by using natural language to frequently iterate over a set of test steps to refine and improve the fidelity and effectiveness of tests

  • Manual to automated test conversion

  • Generate automated tests for a range of different automation tools by analyzing manual test case descriptions already captured in office documents, test management tools or other means of documentation, or by observing real user interactions.

  • Automated UI, API and visual testing

  • Support for automated testing of web, native mobile and desktop applications through the UI, the API and services interfaces. Support for visual testing to highlight crucial changes to an application’s layout and/or content that break the user experience or accessibility requirements. This is achieved via automatic recognition of objects, image, text, audio and video in UIs, like humans do in order to detect quality issues.

  • Self-healing for test scripts

  • Automatically detect why a test case failed and recommend a fix (minimum capability) or automatically update the test case to fix the issue.

  • Test orchestration and prioritization

  • Orchestrate test execution through integrations across development, delivery and execution environments. Additionally, prioritize, optimize and parallelize the execution of tests based on criteria such as reliability (flakiness) of tests or code affected by changes as well which browsers and end-user devices have been updated (change impact analysis) to optimize DevOps workflows.

  • Defect prediction

  • Identify gaps in quality and defect targets, minimize redundancy and improve the effectiveness and efficiency of testing processes by detecting patterns in historical quality assurance (QA) data.

References: