Abstract: Systems and methods may generate code, for a model, with one or more service access points generated and at locations in the code based on an analysis of model constraints and deployment specifications (e.g., RTE specifications or OS specifications). The systems and methods may analyze the model and identify a functionality that needs an RTE service. The system and methods may receive deployment specifications. The systems and methods may generate code for the model, where an analysis of model constraints and the deployment specifications determine which service access points are generated and where in the code the service access points are located. In an embodiment, the code may be executed by different RTEs. In an embodiment, the systems and methods may determine, based on the analysis of the model constraints and the deployment specification, one or more admissible implementations for an RTE service that may be implemented in different ways.

Abstract: A method and system automatically generates a display of symbolic equations from a graphical model (or vice versa) which is readable, parametric, and interactive.

Abstract: Systems and methods may generate code, for a model, with one or more service access points generated and at locations in the code based on an analysis of model constraints and deployment specifications (e.g., RTE specifications or OS specifications). The systems and methods may analyze the model and identify a functionality that needs an RTE service. The system and methods may receive deployment specifications. The systems and methods may generate code for the model, where an analysis of model constraints and the deployment specifications determine which service access points are generated and where in the code the service access points are located. In an embodiment, the code may be executed by different RTEs. In an embodiment, the systems and methods may determine, based on the analysis of the model constraints and the deployment specification, one or more admissible implementations for an RTE service that may be implemented in different ways.

Abstract: Systems and methods may generate code, for a model, with one or more service access points generated and at locations in the code based on an analysis of model constraints and deployment specifications (e.g., RTE specifications or OS specifications). The systems and methods may analyze the model and identify a functionality that needs an RTE service. The system and methods may receive deployment specifications. The systems and methods may generate code for the model, where an analysis of model constraints and the deployment specifications determine which service access points are generated and where in the code the service access points are located. In an embodiment, the code may be executed by different RTEs. In an embodiment, the systems and methods may determine, based on the analysis of the model constraints and the deployment specification, one or more admissible implementations for an RTE service that may be implemented in different ways.

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: Processing external code includes: parsing the external code to identify a first semantic entity, mapping the first semantic entity to a second semantic entity, the first semantic entity comprising a first set of one or more specified attributes and the second semantic entity comprising a second set of one or more attributes that are capable of being specified, determining that a first attribute of the second set of one or more attributes does not have a corresponding specified attribute within the first set of one or more specified attributes, determining available information for specifying the first attribute of the second set of one or more attributes, and storing the second semantic entity in association with the first attribute of the second set of one or more attributes specified based on user selection or specifying the first attribute in response to available information provided to a user interface system.

Abstract: Processing external code includes: parsing the external code to identify a first semantic entity, mapping the first semantic entity to a second semantic entity, the first semantic entity comprising a first set of one or more specified attributes and the second semantic entity comprising a second set of one or more attributes that are capable of being specified, determining that a first attribute of the second set of one or more attributes does not have a corresponding specified attribute within the first set of one or more specified attributes, determining available information for specifying the first attribute of the second set of one or more attributes, and storing the second semantic entity in association with the first attribute of the second set of one or more attributes specified based on user selection or specifying the first attribute in response to available information provided to a user interface system.

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 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 device may obtain a model. The model, when executed, may simulate a behavior of a physical system. A user, such as, for example, an engineer, may specify a design interest for the model. The design interest may be associated with a particular behavior of a portion of the model. The device may analyze the model based on the design interest and may determine, based on analyzing the model, a group of model elements, included in the model, that are related to the design interest. The device may generate, based on the group of model elements, a model slice. When the model slice is executed, a behavior of the model slice may correspond to the particular behavior of the portion of the model. The device may analyze the particular behavior of the portion of the model based on executing the model slice.

Abstract: A system and method creates a plurality of different ring components for a referenced model included within a parent model. The ring components include values for one or more model-level, block-level, and signal-level attributes of the referenced model. One or more ring components are selected and assigned to the referenced model in the context of the parent model. During execution of the parent model, information from the selected ring component is accessed and used to control execution of the referenced model. During code generation for the parent model, information from the selected ring component is accessed and used to control the code generation process for the referenced model.

Abstract: A computing device may include a memory to store data that describes a state machine model that includes destination states and source states. The source states may be associated with conditions upon which the state machine model is to transition from a corresponding source state to one of the destination states. The device may also include a processor configured to generate data to describe a state diagram from the data that describes the state machine model. The state diagram may include the graphical symbols and lines. Each of the graphical symbols may represent one of the source states or one of the destination states. The lines may represent transitions and include one or more vertical lines to represent transitions to one of the destination states from more than one of the source states. The graphical symbol may represent the one of the destination states is not adjacent to the graphical symbols to represent the more than one of the source states.

Abstract: Systems and methods generate code from an executable model. The model may operate on variables having floating point data types. The systems and methods may unpack the sign, exponent, and mantissa components of the floating point variables, and interpret them as boolean, integer, or fixed-point data types. The systems and methods may include operators that operate on the extracted sign, exponent, and mantissa components, and that produce sign, exponent, and mantissa outputs having boolean, integer or fixed-point data types. The systems and methods may pack the sign, exponent, and mantissa components of the output into an integer and reinterpret the integer as a floating point data type. Having replaced the floating point data types with boolean, integer or fixed-point data types, the generated code may be suitable for programmable logic devices and/or microcontrollers that lack Floating Point Units (FPUs).

Abstract: A device may receive input code that includes one or more input objects. The input code may be used in connection with generation of output code. The output code, when generated, may include one or more output objects, corresponding to and different than the one or more input objects. The device may receive or determine conversion information identifying a conversion operation to perform to generate the one or more output objects based on the one or more input objects. The conversion information may be received separately from the input code. The device may generate, based on the conversion information and the input code, an intermediate representation. The intermediate representation may include one or more annotations corresponding to the one or more input objects and defining the conversion operation. The device may compile, based on the intermediate representation, the output code. The device may execute or provide the output code.

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: Systems and methods generate code from an executable model. The model may operate on variables having floating point data types. The systems and methods may unpack the sign, exponent, and mantissa components of the floating point variables, and interpret them as boolean, integer, or fixed-point data types. The systems and methods may include operators that operate on the extracted sign, exponent, and mantissa components, and that produce sign, exponent, and mantissa outputs having boolean, integer or fixed-point data types. The systems and methods may pack the sign, exponent, and mantissa components of the output into an integer and reinterpret the integer as a floating point data type. Having replaced the floating point data types with boolean, integer or fixed-point data types, the generated code may be suitable for programmable logic devices and/or microcontrollers that lack Floating Point Units (FPUs).

Abstract: A computer-readable memory device may include instructions to store data describing a state machine model including source states and destination states. The device may also include instructions to store, for each of the source states, a condition field identifying a condition upon which, when satisfied, the state machine model transitions from the source state to one of the destination states. The device may also include instructions to store, for each of source states, a destination field identifying the one of the destination states. Each of at least two of the source states may identify an identical destination state in the corresponding destination field. Each of at least two of the source states may identify an identical condition in the corresponding condition field.

Abstract: A system and method automatically generating one or more message view windows or panes based on an analysis of the execution behavior of a model, such as a computer-generated, executable graphical model. A model analyzer examines execution instructions including schedules generated for the model and the sending and receiving of messages by model components or elements. An auto diagram builder generates the one or more message view windows that includes graphical affordances representing at least some of the messages. The messages may be presented in the one or more message view windows in the order of the occurrence of the messages during execution of the model.

Abstract: A device may receive input code that includes one or more input objects. The input code may be used in connection with generation of output code. The output code, when generated, may include one or more output objects, corresponding to and different than the one or more input objects. The device may receive or determine conversion information identifying a conversion operation to perform to generate the one or more output objects based on the one or more input objects. The conversion information may be received separately from the input code. The device may generate, based on the conversion information and the input code, an intermediate representation. The intermediate representation may include one or more annotations corresponding to the one or more input objects and defining the conversion operation. The device may compile, based on the intermediate representation, the output code. The device may execute or provide the output code.