OpenText Functional Testing and Qt Squish compete in automated testing solutions. OpenText offers significant savings in automation, giving it an edge. In contrast, while Qt Squish has a simpler setup, it requires a considerable upfront cost.
Features: OpenText Functional Testing provides extensive AI-driven test automation support, comprehensive integration options including with Jira, and significant automation cost savings. Qt Squish supports a wide range of platforms including desktop, mobile, and web, offers an integrated development environment, and allows for remote testing with a focus on behavior-driven development.
Room for Improvement: OpenText Functional Testing could be more price accessible and improve support for diverse UI controls. It would benefit from enhancements in cost-effectiveness for small teams. Qt Squish could refine its pricing structure and improve initial cost barriers. Its licensing model could be more flexible and comprehensive documentation could enhance user onboarding.
Ease of Deployment and Customer Service: OpenText Functional Testing is noted for its ease of integration with existing systems and user-friendly interfaces. Qt Squish is praised for a straightforward setup and efficient technical support, directly involving developers and designers in problem-solving, contributing to its user-friendly nature.
Pricing and ROI: OpenText Functional Testing is seen as a costly option but provides significant reductions in manual testing expenses. Qt Squish requires substantial initial investment yet offers noticeable returns across different platforms. Qt Squish provides a simpler licensing model compared to OpenText's flexible pricing models.
For the part that has been automated in Qt, not everything is suitable for automation.
Initially, it was quite poor, but it seems they are making efforts to improve.
For technical support, I would give them an eight because whenever we have a concern, they immediately reach out to us.
With one license, just one user or one test scenario can be run at a time.
We regularly update the product, and overall, it is stable.
In some cases, object recognition is not 100%, and a customized solution is necessary.
If you want to run it for different versions of the software, then you need the Qt version of Java.
The price of OpenText UFT Developer is a bit higher than expected, but there are no better tools available for a valid comparison.
For the developer license, it is about $5200 a year.
OpenText UFT Developer is user-friendly and integrates well with Visual Studio.
For the parts that have been automated in Qt, not everything is suitable for automation.
| Product | Mindshare (%) |
|---|---|
| OpenText Functional Testing for Developers | 2.9% |
| Qt Squish | 2.5% |
| Other | 94.6% |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 12 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 2 |
| Large Enterprise | 9 |
OpenText Functional Testing for Developers offers robust automation capabilities with support for complex algorithms, multi-platform testing, and developer-friendly integration using C# and Java, facilitating seamless testing transitions and efficient automation workflows.
This testing tool is highly valued for its integration with ALM and Jenkins, along with its developer-focused environment adaptable to Eclipse and Visual Studio. With AI-based object recognition, an object repository, and test framework integration, it bolsters DevOps practices while reducing IT workloads. Supporting UFT to LeanFT transition, it caters to SAP, Java, .NET environments, and more. Enhanced with stable automation, extensive protocol support, and both on-premises and cloud deployments, it targets performance, regression, and functional testing, while recording and screengrabs enhance automation capabilities. Future improvements could include expanded browser compatibility, enhanced JavaScript and mobile support, and better object recognition.
What are the key features of OpenText Functional Testing for Developers?Organizations implement OpenText Functional Testing for complex test automation on desktop, web, and banking applications, supporting performance, regression, and functionality testing across environments like SAP, Java, and .NET. UFT aids in GUI, infrastructure, and ERP application automation, with deployment options including on-premises and cloud implementations. Enhanced screengrabs and recording features aid in practical test case development, while addressing emerging technology needs is a focus.
Qt Squish is a versatile testing tool that supports Python, integrates with Rational Quality Manager, and handles multiple toolkits. It efficiently boosts code quality with features like auto-completion and a comprehensive dashboard while supporting diverse languages and providing strong documentation.
Qt Squish is known for its robust capability in automatic testing, particularly in GUI and regression testing applications across real-time control, embedded systems, and hybrid frameworks. The tool enables behavior-driven development with Gherkin Syntax, integrates seamlessly with CI/CD pipelines, and facilitates effective data-driven and distributed batch testing. Users gain significant value from its compatibility with Qt applications, multiple platforms, extensive language support, and integration with other development tools. Although there are suggestions for improving reporting, configuration for less technical users, Git integration, and object identification, Qt Squish still stands out for its exceptional capability in mapping UI components and supporting automated UI testing.
What are the important features of Qt Squish?Industries such as real-time traffic control, embedded systems, and hybrid applications frequently use Qt Squish for automated testing. The ability to integrate with CI/CD pipelines and compatibility with multiple scripting languages makes it an ideal solution for organizations focusing on GUI and regression testing. Companies benefit from its seamless integration with diverse data sources and development tools, enabling efficient automated UI testing across all relevant platforms.
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