OpenText Functional Testing and Qt Squish are prominent competitors in the field of functional and automated testing tools. While both offer extensive test automation capabilities, Qt Squish seems advantageous in testing Qt applications due to its strong integration and support for various UI technologies.
Features: OpenText Functional Testing stands out for its comprehensive compatibility across tools and technologies, including GUI, database, and API testing. It supports a wide range of applications such as Oracle and SAP, along with built-in functionalities for GUI extension testing and database testing. Qt Squish, however, focuses on superior integration with Qt applications and offers robust GUI component mapping and automation tools, which help in maintaining platform independence and support a range of UI technologies.
Room for Improvement: OpenText Functional Testing could benefit from better browser compatibility and enhanced IDE performance. There are also opportunities for improving .NET application handling, memory usage, and parallel execution capabilities. For Qt Squish, enhancements in test code maintenance and Git integration could improve user experience. Additionally, streamlining the setup process for continuous integration tools would be beneficial for both options.
Ease of Deployment and Customer Service: OpenText Functional Testing offers flexible deployment options on both on-premises and cloud environments, although users encounter difficulties with customer service, citing slow response times and a complex support structure. Qt Squish, primarily an on-premises solution, receives generally positive feedback for its effective technical support despite associated costs.
Pricing and ROI: OpenText Functional Testing is positioned at a high price point but offers good ROI due to its extensive capabilities. Although its licensing terms can be complex, it provides value through broad test automation. Qt Squish also incurs a significant cost, which might pose challenges for smaller teams. Nevertheless, it delivers solid value for projects using Qt, benefiting from a simpler licensing model while offering considerable ROI by reducing manual testing tasks effectively.
The development time using UFT can be cut down into half as compared to coding from scratch.
Automation is done very fast, leading to improvements in the QA process and reducing the time needed for test automation.
We can easily achieve a return on investment in one, two, or three years.
For the part that has been automated in Qt, not everything is suitable for automation.
Organizations can't wait for this lengthy process, especially when they are under pressure with their timelines.
Support cases are easily created and attended to promptly, depending on urgency.
The technical support is rated eight out of ten.
Running them in parallel allows you to consume multiple runtime licenses and just execute the tests that don't have conflicting priorities and get through a lot of volume much quicker.
The tool can be installed on all computers used by developers or test automation engineers.
With one license, just one user or one test scenario can be run at a time.
One of the key stability issues was that Windows would consume memory without releasing it, leading to regression testing crashes.
Incorporating behavior-driven development tests would enhance the capabilities of UFT One.
We frequently encountered stability issues when the browser dependency caused Windows to consume memory without releasing it, leading to crashes during regression testing.
If it could move closer to a no-code or low-code solution, it might dominate the market again.
If you want to run it for different versions of the software, then you need the Qt version of Java.
There are many open-source tools with no cost, and there are no-code tools that are less expensive than UFT.
The pricing or licensing policy of OpenText is a bit expensive, however, it's one of the best solutions in the market.
It's cheaper than Tricentis Tosca but more expensive than some others.
For the developer license, it is about $5200 a year.
UFT supports Oracle, SAP, PeopleSoft, and other non-web applications, making automation feasible.
OpenText Functional Testing has an impressive ability to connect to mobile devices and its ability to test so many different types of software, whether it be mainframe, APIs, mobile, web, or desktop.
The best features of OpenText Functional Testing include descriptive programming, the ability to add objects in the repository, and its ease of use for UI compared to other tools.
For the parts that have been automated in Qt, not everything is suitable for automation.
| Product | Mindshare (%) |
|---|---|
| OpenText Functional Testing | 6.8% |
| Qt Squish | 2.5% |
| Other | 90.7% |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 13 |
| Large Enterprise | 71 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 2 |
| Large Enterprise | 9 |
OpenText Functional Testing provides automated testing with compatibility across technologies, browsers, and platforms. It targets APIs, GUIs, and applications like SAP and Oracle for efficient test automation, emphasizing usability and integration with tools such as Jenkins and ALM.
OpenText Functional Testing offers wide-ranging automation capabilities for functional and regression testing, API testing, and automation across web, desktop, and mainframe applications. It supports script recording and object identification, appealing to less technical users. Despite its advantages, it grapples with memory issues, stability concerns, and a challenging scripting environment. Its VBScript reliance limits flexibility, generating demand for enhanced language support and speed improvement. Users appreciate its role in continuous integration and deployment processes, managing test data efficiently, and reducing manual testing efforts.
What are the key features of OpenText Functional Testing?In industries like finance and healthcare, OpenText Functional Testing is leveraged for end-to-end automation, ensuring streamlined processes and accuracy in testing. Many companies utilize it for efficient test data management and integrating testing within continuous integration/deployment operations.
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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