Method and system for improving efficacy of model verification by model partitioning

A method comprising:

• in a modeling environment in which models are generated in a modeling language,
• receiving an indication that a first composite of model elements, supported by the modeling environment, is selected as a candidate for a rule in partitioning a model that comprises the first composite of model elements, where:
• at least some of the model elements of the first composite of model elements are connected,
• two or more of the model elements of the first composite of model elements comprise a model element associated with a masking operation, an active element and numeric expressions,
• the first composite of model elements is usable as a unit in generating the models or being part of the model in the modeling environment, and
• the first composite of model elements is in the same modeling language as the models generated in the modeling environment;
• analyzing, by one or more processors, the first composite of model elements to determine whether to accept the first composite of model elements as the rule, where:
• the analyzing comprises analyzing a relationship among computations represented by the two or more of the model elements of the first composite of model elements;
• selectively storing, by the one or more processors, the rule in a rule repository based on the analyzing the first composite of model elements;
• selectively providing the rule for use in partitioning the model into testing units for testing the model;
• and
• generating one or more network metrics for testing at least one of the testing units based on one or more rules associated with connectivity of model elements of the at least one of the testing units and one or more element metrics, where the one or more network metrics include a criteria for passing an appropriate value according to the model element associated with the masking operation via the active element of the first composite of model elements,
• wherein
• a first model element of the first composite of model elements and the model element associated with the masking operation are arranged in a dependent configuration according to one or more results from an analysis of the model, wherein the one or more results from the analysis of the model comprise a result of (i) a model element type analysis, (ii) a model element connectivity analysis, and (iii) a model element static dependency analysis and
• the testing coordinates computations represented by the first model element and the model element associated with the masking operation to prevent masking an effect of the first model element based on the generated one or more network metrics.

One or more non-transitory computer-readable media having stored thereon instructions that when executed by a computing device cause the computing device to perform operations comprising:

• for a model comprising model elements, where at least some of the model elements:
• comprise one or more numeric expressions, and
• represent one or more computations,
• analyzing, by one or more processors, the model to identify a first set of model elements that are associated with a model element, where:
• the analyzing comprises analyzing a relationship between one or more computations represented by the first set of model elements and one or more computations represented by the model element, and
• the first set of model elements and the model element form a first network unit that represents a first hierarchy of computation;
• applying, by the one or more processors, one or more results from an analysis of the model to the 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;
• generating, by the one or more processors, a second network unit, representing a second hierarchy of computation, from the first network unit based on the determined complexity of the first network unit or the determined coupling of the first network unit to the other model elements of the model, where the generating comprises modifying the first network unit to form the second network unit by:
• adding one or more additional model elements of the model into the first network unit, or
• removing one or more model elements of the first network unit from the first network unit;
• providing, 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 that include at least one model element associated with a masking operation, at least one active element and at least one numeric expression of the one or more numeric expressions;
• generating one or more network metrics for testing the second network unit based on one or more rules associated with connectivity of the two or more model elements of the second network unit and one or more element metrics, wherein the one or more network metrics include a criteria for passing an appropriate value according to the at least one model element associated with the masking operation via the at least one active element of the second network unit;
• and
• generating one or more tests for the second network unit, wherein
• the two or more model elements of the second network unit include a first model element implementing a first operation,
• the first model element and the at least one model element associated with the masking operation arranged in a dependent configuration according to the one or more results from the analysis of the model, wherein the one or more results from the analysis of the model comprise a result of one of (i) a model element type analysis, (ii) a model element connectivity analysis, and (iii) a model element static dependency analysis;
• and
• the one or more tests for the second network unit coordinate the first operation implemented by the first model element and the masking operation implemented by the at least one model element associated with the masking operation of the second network unit to prevent masking an effect of the first operation by the masking operation, based on the generated one or more network metrics.

An apparatus comprising:

• a memory storing a model comprising model elements, where at least some of the model elements:
• comprise one or more numeric expressions, and
• represent one or more computations;
• and
• one or more processors configured to:
• analyze the model to identify a first set of model elements that are associated with a model element, where:
• the analyzing comprises analyzing a relationship between one or more computations represented by the first set of model elements and one or more computations represented by the model element, and
• the first set of model elements and the model element form a first network unit that represents a first hierarchy of computation;
• apply one or more results from an analysis of the model to the 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;
• generate a second network unit, representing a second hierarchy of computation, from the first network unit based on the determined complexity of the first network unit or the determined coupling of the first network unit to the other model elements of the model, where the generating comprises modifying the first network unit to form the second network unit by:
• adding one or more additional model elements of the model into the first network unit, or
• removing one or more model elements of the first network unit from the first network unit;
• provide the second network unit as a testing unit for testing the model, the second network unit comprising two or more model elements that include at least one model element associated with a masking operation, at least one active element and at least one numeric expression of the one or more numeric expressions;
• generating one or more network metrics for testing the second network unit based on one or more rules associated with connectivity of the two or more model elements of the second network unit and one or more element metrics, wherein the one or more network metrics include a criteria for passing an appropriate value according to the at least one model element associated with the masking operation via the at least one active element of the second network unit;
• and
• generate one or more tests for the second network unit, wherein
• the two or more model elements of the second network unit include a first model element implementing a first operation,
• the first model element and the at least one model element associated with the masking operation arranged in a dependent configuration according to the one or more results from the analysis of the model, wherein the one or more results from the analysis of the model comprise a result of one of (i) a model element type analysis, (ii) a model element connectivity analysis, and (iii) a model element static dependency analysis;
• and
• the one or more tests for the second network unit coordinate the first operation implemented by the first model element and the masking operation implemented by the at least one model element associated with the masking operation of the second network unit to prevent masking an effect of the first operation by the masking operation, based on the generated one or more network metrics.

One or more non-transitory computer-readable media having stored thereon instructions that when executed by a computing device cause the computing device to perform operations comprising:

• in a modeling environment in which models are generated in a modeling language,
• receiving an indication that a first composite of model elements, supported by the modeling environment, is selected as a candidate for a rule in partitioning a model that comprises the first composite of model elements, where:
• at least some of the model elements of the first composite of model elements are connected,
• two or more of the model elements of the first composite of model elements comprise a model element associated with a masking operation, an active element and numeric expressions,
• the first composite of model elements is usable as a unit in generating the models or being part of the model in the modeling environment, and
• the first composite of model elements is in the same modeling language as the models generated in the modeling environment;
• analyzing, by one or more processors, the first composite of model elements to determine whether to accept the first composite of model elements as the rule, where:
• the analyzing comprises analyzing a relationship among computations represented by the two or more of the model elements of the first composite of model elements;
• selectively storing, by the one or more processors, the rule in a rule repository based on the analyzing the first composite of model elements;
• selectively providing the rule for use in partitioning the model into testing units for testing the model;
• and
• generating one or more network metrics for testing at least one of the testing units based on one or more rules associated with connectivity of model elements of the at least one of the testing units and one or more element metrics, where the one or more network metrics include a criteria for passing an appropriate value according to the model element associated with the masking operation via the active element of the first composite of model elements,
• wherein
• a first model element of the first composite of model elements and the model element associated with the masking operation are arranged in a dependent configuration according to one or more results from an analysis of the model, wherein the one or more results from the analysis of the model comprise a result of (i) a model element type analysis, (ii) a model element connectivity analysis, and (iii) a model element static dependency analysis and
• the testing coordinates computations represented by the first model element and the model element associated with the masking operation to prevent masking an effect of the first model element based on the generated one or more network metrics.