Collect Model and Testing Metrics

Collect model metric data and create custom model metrics

You can use model metrics to assess that your model and code comply with size, complexity, and readability requirements. As you test your model against requirements, you can use metrics to assess the status and quality of your requirements-based testing activities. You can use the model metric API to create your own model metrics, compute model and testing metrics, and export metric data. To visualize model metric data and compliance status for your model, use the Metrics Dashboard. Use the Model Testing Dashboard to view metric data on the completeness of requirements, test cases, and test results for your model. To get started, see Collect and Explore Metric Data by Using the Metrics Dashboard and Explore Status and Quality of Testing Activities Using the Model Testing Dashboard.

Classes

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Collect Model Metric Data

`slmetric.Engine`	Collect metric data on models or model components
`slmetric.metric.MetaInformation`	Set metadata for custom metrics
`slmetric.metric.Result`	Metric data for specified model component and metric algorithm
`slmetric.metric.ResultCollection`	Metric data for specified model metric
`slmetric.metric.ResultDetail`	Details about instances of `slmetric.metric.Result` objects
`slmetric.metric.ResultClassification`	Access metric data thresholds results

Customize Metrics Dashboard

`slmetric.config.Configuration`	Specify metric data categories and custom metric families
`slmetric.config.ThresholdConfiguration`	Specify metric and `slmetric.metric.Result` property for thresholding
`slmetric.config.Threshold`	Object for holding metric result thresholds
`slmetric.config.Classification`	Specify categorical metric data ranges
`slmetric.config.MetricRange`	Specify metric data threshold values
`slmetric.dashboard.Configuration`	Object containing information on Metrics Dashboard layout and widgets
`slmetric.dashboard.Container`	Widget for holding `slmetric.dashboard.Widget` and `slmetric.dashboard.CustomWidget` objects in Metrics Dashboard
`slmetric.dashboard.CustomWidget`	Object for holding custom Metrics Dashboard widgets
`slmetric.dashboard.Group`	Widget for holding `slmetric.dashboard.Container`, `slmetric.dashboard.Widget` and `slmetric.dashboard.CustomWidget` objects on Metrics Dashboard
`slmetric.dashboard.Layout`	Create object for holding Metrics Dashboard customizations
`slmetric.dashboard.Widget`	Object for holding Actual/Potential Reuse, System Interface, or System Info widgets

Create Custom Model Metric

`Advisor.component.Component`	Create component for metric analysis
`Advisor.component.Types`	Create `enum` class specifying component type
`slmetric.metric.Metric`	Abstract class for creating model metrics

Collect Metric Data on Model Testing Artifacts

`metric.Engine`	Collect metric data on model testing artifacts
`metric.Result`	Metric data for specified metric algorithm and requirements-based testing artifacts

Functions

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Collect Model Metric Data

`metricsdashboard`	Open Metrics Dashboard
`slmetric.metric.getAvailableMetrics`	Obtain available metrics

Customize Metrics Dashboard

`slmetric.config.getActiveConfiguration`	Obtain file path and name of XML file containing active Metrics Dashboard custom configuration
`slmetric.config.setActiveConfiguration`	Activate custom configuration for metric engine to use
`slmetric.dashboard.setActiveConfiguration`	Activate custom metric dashboard layout
`slmetric.dashboard.getActiveConfiguration`	Obtain file path and name of XML file containing active Metrics Dashboard layout

Create Custom Model Metric

`slmetric.metric.createNewMetricClass`	Create new metric class for a custom model metric
`slmetric.metric.registerMetric`	Register a custom model metric with the model metric repository
`slmetric.metric.unregisterMetric`	Unregister a custom model metric from the model metric repository
`slmetric.metric.refresh`	Update available model metrics

Collect Metric Data on Model Testing Artifacts

modelTestingDashboard Open Model Testing Dashboard

Topics

Model Metrics

Collect and Explore Metric Data by Using the Metrics Dashboard

Collect and view metric data for quality assessment.

Customize Metrics Dashboard Layout and Functionality

Configure compliance metrics, add metric thresholds, and customize Metrics Dashboard layout.

Collect Model Metrics Programmatically

Use the model metric API to programmatically collect metrics for a model, such as subsystem and block counts.

Model Metrics

Model metrics provided by MathWorks that return metric data on your model for size, complexity, readability, and compliance to standards and guidelines.

Model Metric Data Aggregation

Options for defining model metric data aggregation and returning aggregated model metric results.

Create a Custom Model Metric for Nonvirtual Block Count

Create a new model metric by using the slmetric.metric.createNewMetricClass function and defining the metric algorithm.

Identify Modeling Clones with the Metrics Dashboard

You can use the Model Metrics Dashboard tool to enable subsystem reuse by identifying exact graphical clones across a model hierarchy.

Collect Model Metrics Using the Model Advisor

Assess model size, complexity, and readability, using the Model Advisor to run model metric checks.

Collect Compliance Data and Explore Results in the Model Advisor

This example shows how to collect model metric data by using the Metrics Dashboard and explore detailed compliance results and, fix compliance issues by using the Model Advisor.

Collect Metric Data Programmatically and View Data Through the Metrics Dashboard

This example shows how to use the model metrics API to collect model metric data for your model, and then explore the results by using the Metrics Dashboard.

Fix Metric Threshold Violations in a Continuous Integration Systems Workflow

Use a continuous integration workflow to investigate whether your model violates metric threshold values.

Compare Model Complexity and Code Complexity Metrics

Assess the complexity of your system in model-based design.

Requirements-Based Testing Metrics

Explore Status and Quality of Testing Activities Using the Model Testing Dashboard

Evaluate the status and quality of model testing in your project.

Fix Requirements-Based Testing Issues

Fix model testing quality issues by using the Model Testing Dashboard.

Model Testing Metrics

Model testing metrics provided by MathWorks that return metric data on your model for implementing and testing requirements.

Manage Requirements-Based Testing Artifacts for Analysis in the Model Testing Dashboard

Set up and manage a project that uses the Model Testing Dashboard.

Collect Metrics on Model Testing Artifacts Programmatically

Use a script to assess the quality of your requirements-based testing.

Assess the Completeness of Requirements-Based Testing in Accordance with ISO 26262

Use the Model Testing Dashboard to analyze the completeness and quality of requirements-based testing activities in accordance the ISO 26262 standard.