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Your feedback is crucial in shaping |
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Xray's roadmap |
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Our release plan is available in our Jira issue tracker. Feel free to view and to vote on the issues that you would like to see implemented (account registration required).
Here you can find a list of features that define our main goals for future releases. This doesn't mean that other, potentially smaller features, won't be implemented as well.
Shipped
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| title | Test Run custom fields |
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You can now define additional custom fields for Test Runs. These fields can be useful to add extra information to Test Runs usually only available during or after executing Tests.
Test Run custom fields can be configured by project and by Test Type. Therefore, these settings will not affect other projects within your Jira instance. For example, it is possible to have custom fields just for Manual Tests within a project.
Reporting
The Test Runs List report and gadget can already display Test Run Custom Field values for each Test Run.
Within a Test Execution issue, it is also possible to display Test Run Custom Field columns and to filter Test Runs by Test Run Custom Field values.
Learn more about Test Run Custom Fields here.
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| title | Parameterized Tests and data driven testing |
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Test parameterization is a powerful practice that allows the same test to be executed multiple times with different parameters. Parameters are similar to input values (variables) that can change with each execution.
Parameterized tests in Xray are defined just like any other test with the addition of some parameter names within the specification using the following notation: ${PARAMETER_NAME}. This notation is used to reference parameters within the test steps.
Precondition issues can also be parameterized by including parameter names in the precondition specification.
The parameters, along with their values, are defined within a dataset. A dataset is a collection of data represented with a tabular view where every column of the table represents a particular variable (or parameter), and each row corresponds to a given record (or iteration) of the dataset. The number of rows in the dataset determines the number of iterations to execute.
A dataset can be defined in the following entities/scopes:
- Test (default dataset)
- Test Plan - Test
- Test Execution - Test (Test Run)
The closest dataset to the test run will be the one used to generate the iterations, effectively overriding any dataset defined in higher levels.
All iterations for a given test are executed within the context of the same test run. Each iteration can be expanded, and the steps executed individually. The step parameters will be replaced by the corresponding iteration values. The steps affect the iteration status that, in turn, affects the overall test run status.
Learn more about parameterized tests here.
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| title | Modular Tests |
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Modular test design is a way of promoting test case reusability and composition across a large test repository. To design modular tests, you can create a test where some of the steps call or include other test cases. This prevents testers from having to write the same steps over and over again in different high-level tests. Using a modular design approach, any test can become a building block of more extensive test scenarios. Still, they can also be executed individually if needed.
A called test can, in turn, also call other tests. You can compose a test scenario with up to five levels of depth.
Modular tests can also be parameterized. When calling a test, you can provide new parameter values according to the parent test data.
Upon executing, Xray will unfold all called test steps in the test run. This becomes transparent to testers as they only have to follow and execute the steps on the execution, even though test steps might come from different tests issues.
A common use case for modular tests is end-to-end testing. End-to-end tests often need to pass through the same area or component of the application before asserting the final result. With modular test design, you can reuse the tests for these common areas or components.
Learn more about modular tests here.
In the works
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Wish list for future versions
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| title | Daily history coverage report |
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. It helps us define our vision and priorities for upcoming releases, ensuring that new features align with what matters most to you. Below, you will find the latest updates on what's in progress and what's coming soon. This list isn’t exhaustive—new enhancements and bug fixes may be added along the way based on your needs. Please note that the content on this page, including the roadmap, is subject to change and may be updated based on evolving priorities and requirements. |
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