Abstract:
A device may analyze, by one or more processors, a model to identify a first set of model elements that are associated with a model element. The device may apply, by the one or more processors, one or more results from an analysis of the model to a first network unit to determine a complexity of the first network unit or a coupling of the first network unit to other model elements of the model. The device may generate, by the one or more processors, a second network unit, representing a second hierarchy of computation, from the first network unit based on the complexity or the coupling. The device may provide, by the one or more processors, the second network unit as a testing unit for testing the model, the second network unit comprising two or more model elements and one or more numeric expressions.
Abstract:
An embodiment includes a computer-readable media storing instructions that when executed on processing logic execute a process for reducing complexity. The media stores instructions for identifying data dependencies in a model having executable semantics, the data dependencies affecting verification of the model and for selecting a location in the model, the location having data dependencies with other locations in the model, the location to be verified when the model is verified. The media also stores instructions for detecting complexities in the model, the complexities related to the selected location and presenting information about a source for at least one of the complexities. The media further stores instructions for eliminating the source for the at least one of the complexities and for transforming the model into an updated model based on the eliminating, the updated model not including the source for the at least one of the complexities.
Abstract:
An embodiment can include one or more computer-readable media storing executable instructions that when executed on processing logic process variable signals. The media can store one or more instructions for receiving executable code that includes constructs with variable signals for processing the variable signals, and for performing a coverage measurement on the executable code based on information about one or more of the variable signals processed by the executable code. The media can store one or more instructions for producing a coverage result based on the coverage measurement, the coverage result identifying a degree of coverage for the executable code when the executable code processes the variable signals.
Abstract:
A computer-based model having executable semantics may be used to simulate the behavior of a system. A substructure of interest is sliced from the model and analyzed to determine a transformation of the slice while preserving some context of the model. The transformed slice may be further manipulated outside of the model, integrated back into the model in place of the original slice, or used in other ways.
Abstract:
A system and method generates contextual information for a source model. An identification of one or more first model elements of interest within the source model may be received. One or more constraints on inputs of selected model elements also may be received. A scope of analysis regarding outputs of the first model elements may be specified. The contextual information may be derived automatically for the one or more first model elements. The contextual information may include one or more model elements, signals, or states that are contained with the scope of analysis while execution of the source model is limited by the one or more constraints. The derived contextual information may be provided to an output device.
Abstract:
A system and method extends model verification through the creation of composite test objectives. A composite objective includes two or more logically or temporally combined standard or basic test objectives. The basic test objectives selected to form a composite test may be automatically generated by the system or method, or they may be custom defined. A composite test objective represents a new coverage objective that extends model coverage analysis beyond the coverage that is available with the basic test objectives. The system and method also automatically generates one or more test cases for achieving the composite objective. The test cases include input data values for the model, and may cause the specified logical or temporal combination of basic test objectives to evaluate to true at least once during simulation of the model or according to the temporal combination.
Abstract:
A system and method generates a contextual model for a source model. The system and method receives a designation of a component of interest in the source model. The system and method analyzes the source model and identifies those model elements within the source model that have an interaction behavior with the component of interest. The system and method includes the component of interest and the model elements having the interaction behavior with the component of interest in the contextual model. The system and method connects the model elements to the component of interest in the context model in a similar manner as in the source model. The context model may be run or evaluated.
Abstract:
A system and method generates a contextual model for a source model. The system and method receives a designation of a component of interest in the source model. The system and method analyzes the source model and identifies those model elements within the source model that have an interaction behavior with the component of interest. The system and method includes the component of interest and the model elements having the interaction behavior with the component of interest in the contextual model. The system and method connects the model elements to the component of interest in the context model in a similar manner as in the source model. The context model may be run or evaluated.
Abstract:
A system and method extends model verification through the creation of composite test objectives. A composite objective includes two or more logically or temporally combined standard or basic test objectives. The basic test objectives selected to form a composite test may be automatically generated by the system or method, or they may be custom defined. A composite test objective represents a new coverage objective that extends model coverage analysis beyond the coverage that is available with the basic test objectives. The system and method also automatically generates one or more test cases for achieving the composite objective. The test cases include input data values for the model, and may cause the specified logical or temporal combination of basic test objectives to evaluate to true at least once during simulation of the model or according to the temporal combination.
Abstract:
Exemplary embodiments employ a mapping among entities that are related to each other. The entities may include a graphical model, generated code, a generated report, a requirements document and/or an intermediate representation. The mapping may facilitate graphical identifications between parts of one entity that maps to part of another entity. The graphical identification may occur based on a selection of a part in one of the entities.