This determines how the model is created, as well as the options available within the model editor. It further determines the default coverage profile for the model.
Freestyle Models
In a Freestyle model, the last tab on the menu ribbon is Test Generation, and the Coverage Profile defaults to Default Profile.
The tab before that is Test Data & Automation, and you are able to add test automation options.
Requirements Models
In a Requirements model, the last tab is Requirements, and the Coverage Profile defaults to User Stories.
The tab before that is Test Data. You only have the Variables and Assignment options.
Changing Model Types After Creation
You can change the model type after creation green type identifier at the top of the window
When you click on this, a dropdown dialogue appears and you can select another type:
Model Versions Explained
Several versions can be associated with a given model. Additionally, if you remove a Start Node or End Node, you will be forced to create a new Model version. This is to prevent breaking any subflow dependencies, i.e. if an end node that is used to link to another subflow within a Master Model is removed, then the master model will break.
Each time a model is saved, it is saved either to an existing model version, or a new version is created. Model versions do not appear in the Test Modeller “Models” workspace, but are available to be viewed once the model has been opened in the Model Editor.
To browse between versions of an open model, click the “Version” button in the home tab of the menu. To open and edit a given Version, click the eye icon next to it:
A Model is a canvas and the Flow that is built onto it. Freestyle - This is the most commonly used and most flexible of Model types. Use this type as the master Flow. There are Test Data & Automation and Test Generation tabs.
A Model is a canvas and the Flow that is built onto it. Requirement - Designed for BAs and Product owners. This Model type helps to build Flows that can then be converted to Jira, Gherkin or other requirement management software. There are Test Data and Requirements tabs.
A Model is a canvas and the Flow that is built onto it. Test Design - Designed for manual test cases. It is similar to Freestyle. It has Test Data & Automation and Test Generation tabs.
A Model is a canvas and the Flow that is built onto it. Automation - Designed for creating Automated Test Cases. This Model type is used to define Automation Flows, and links well with Selenium and other automation software. It has Test Data & Automation and Test Generation tabs.
A Data Model is used to generate test data. Rather than showing the step-by-step nature of a Linear model or the if-then-else style of a Non-Linear Model, a Data Model shows the possible data that could exist in a List or a database, and allows the generation of data to fit a test case. Rules, Tags, and Coverage can be used to control the generation of data to fit a Test Case.
A Start Node is a trigger that occurs at the start of a model. To use one, drag it from the Actions panel onto the Model canvas.
The End Node is the event that terminates the model. To use one, drag it from the Actions panel onto the Model canvas. There can be more than one End Node, each controlling for a unique outcome.The journey through the Flow ends at an End Node. Where a Model is used as a Subflow within another Model, the End Nodes become the outward connection to the master Model.
A Model is a canvas and the Flow that is built onto it. There are several types of Model, some of which display different tabs and tools on the toolbar in Test Modeller.
The Master Model is simply a model which combines Subflows into one large Model. Master Models are used to join together a range of system models, visualise them and test them as a whole.
Test Modeller is Curiosity's flow-driven model-based tool which provides a range of accelerators and connectors for building flowcharts rapidly. This includes importers for existing requirements and test cases, as well as recordings and scans of already built systems. These accelerators are designed to significantly reduce the time and technical knowledge needed to model complex systems, unlocking the value of model-based test automation.
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