

OpenText Functional Testing and Eggplant Test both compete in automated software testing. OpenText holds an advantage in object recognition and platform compatibility, while Eggplant excels in image recognition and scriptless testing.
Features: OpenText Functional Testing supports a wide range of platforms and technologies, provides extensive browser support, and excels in both GUI and API testing. Eggplant Test offers advanced image recognition and Optical Character Recognition (OCR), enabling robust cross-platform testing and AI-driven, scriptless testing.
Room for Improvement: OpenText needs enhancements in resource consumption, integration complexity, and scripting ease. Browser compatibility can also improve. Eggplant could use improved documentation, a more user-friendly interface, and better complex script support. Expanding integration with other tools and reducing cost would boost its appeal.
Ease of Deployment and Customer Service: OpenText primarily offers on-premises deployment with private cloud options, facing mixed customer service reviews. Eggplant provides flexible deployment with both on-premises and public cloud options, albeit with lower-rated customer service due to delays and costs.
Pricing and ROI: OpenText has high licensing costs, justified by extensive capabilities and support, with substantial ROI due to automation benefits. Eggplant, although also costly, emphasizes its support and stability, ensuring high ROI through reduced testing time and increased accuracy, especially for enterprises with large testing volumes.
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.
I'm not impressed because it depends on the resolution of the screen, so I wouldn't highly recommend this tool.
Eggplant Test offers 24x7 support.
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.
One of the key stability issues was that Windows would consume memory without releasing it, leading to regression testing crashes.
For big problems and complex automation tasks, I would prefer UFT because it has more flexibility and is more effective.
The two-system architecture that we currently follow could be better replaced with a one-system architecture.
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.
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.
It can auto-heal the test cases and suggest new paths for testing, enhancing our ability to automate end-to-end journeys across various applications.
It can integrate with GitHub, allowing you to work with DevOps pipelines, so whenever you make changes in GitHub, it runs and checks the smoke testing on the server.
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.
| Product | Market Share (%) |
|---|---|
| OpenText Functional Testing | 7.9% |
| Eggplant Test | 3.8% |
| Other | 88.3% |


| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 3 |
| Large Enterprise | 14 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 13 |
| Large Enterprise | 71 |
Across every industry, digital transformation is top of mind. New methods of developing software are driving fast change, and test teams are feeling the pressure. Increasing demand to release faster while maintaining the highest levels of quality is making the testing process more complex and harder to scale.
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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.
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