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Parameters are defined within datasets. However, it is possible to reference a parameter that is not yet defined (meaning it does not have a corresponding name within the dataset). In this case, the parameter will be highlighted in red.
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Currently, the test parameterization feature is only available for Manual Tests. Xray will support defining parameters and use datasets on BDD and generic test types as well. |
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Dataset scopes
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The test dataset is the default. If there is the need to override or change this dataset you can do this at the planning or execution phases.
Dataset limits
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The parameters will be unfolded on the execution screen, just like Test cases. For this, the dataset must have the same parameters, matched by name.
Execution
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.
TODO: link to execution page
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- Create or edit a given step using either the inline view within the test issue or the steps dialog.
- When specifying a step, to reference a parameter you have two options:
- Start typing ${. If there is a default dataset defined on the test, you should see a list of the available parameters. Choose the desired parameter using the cursor keys or mouse. The parameter will be placed with the text.
- Use the toolbar button ${. After pressing this button, and if there is a default dataset defined on the test, you should see a list of the available parameters. Choose the desired parameter using the cursor keys or mouse. The parameter will be placed on the cursor position.
Creating a dataset
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a. create an ad hoc list just for this parameter. You need to specify the values for the list.
b. use a project predefined list.
2.5. Press "Save" to create the parameter. The parameter must be placed on the dataset.
3. Adding combinatorial parameter values:
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3.1. For text parameters, just type the value and press the check button next to the field.
3.2. For list parameters, select an option and press the check button next to the field.
4. Adding rows (filling the parameter values):
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You can navigate between cells of the same row and also between rows using the keyboard: TAB (forward), SHIFT+TAB (backward).
4.2. To create new rows, you can press the "New" button below the table or navigate using the keyboard from the last row (a new row will be created automatically by navigating forward on the last cell of the last row).
5. Converting a seeding parameter to a combinatorial parameter:
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5.1. Next to each column, there is an options button. Clicking this button will reveal a menu with options for Editing, Deleting, and Converting parameters.
5.2. Click on "Convert to combinatorial parameter."
6. Converting a combinatorial parameter to a seeding parameter:
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6.1. Next to each combinatorial column, there is an options button. Clicking this button will reveal a menu with options for Editing, Deleting, and Converting parameters.
6.2. Click on the "Convert to non-combinatorial parameter".
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7.1. Next to each combinatorial column, there is an options button. Clicking this button will reveal a menu with options for Editing, Deleting, Converting parameters, and Generating all combinations.
7.2. Click on the "Generate all combinations." A confirmation dialog will appear. Confirming the changes will apply the cartesian product between the combinational parameter values and the seeding parameter rows.
8. After having performed all changes in the dataset, you need to press the "Save" button in order to persist the dataset into the database.
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- Create new parameters - If checked, it will create non-existing parameters automatically, based on the CSV column name. Otherwise, it will just append/update the values on the existing parameters.
4. Press "Import" to import the external dataset.
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2.2. Open the dataset dialog by selecting the "Dataset" action from the test row options menu.
3. The dataset dialog is opened.
3.1. If there is a dataset defined on a parent level, it is possible to Override the parent dataset and modify its values.
3.2. Otherwise, you can start defining a new dataset at this level.
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