Graphical Model Test Entities for Verification Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing graphical modeling and verification tools face challenges in efficiently configuring and interpreting verification scenarios for model-based designs, as they often require extensive resource-intensive setups and result in inconveniently formatted outputs that are difficult to relate back to the original graphical model.
Innovation Solution
The introduction of a design element in the graphical model to represent and enforce conditions, allowing for the validation of model portions by assuming satisfied or unsatisfied statuses, which can be used to determine the satisfaction of other conditions, thereby streamlining the verification process and improving the alignment of verification results with the model-based design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive verification scenarios are run in a verification tool, then verification coverage is improved, but time consumption and resource usage increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-configuring test cases and verification scenarios before execution. Test cases are prepared with expected results and verification scenarios are set up in advance, allowing the verification tool to execute comprehensive checks more efficiently without requiring manual configuration during runtime, thus reducing overall time consumption while maintaining thorough verification coverage
Solution Approach 2:
The patent implements feedback mechanisms where verification results are automatically fed back to update test case priorities and refine verification scenarios. This iterative feedback loop allows the system to focus computational resources on high-impact verification areas, improving verification coverage efficiency and reducing unnecessary time spent on low-value verification paths
2Reliability
If verification scenarios are configured in a verification tool with different configuration environment and language, then verification capability is improved, but difficulty in relating verification results to the graphical model increases
Solution Approach 1:
The patent introduces an intermediary layer in the form of a test case management system that bridges the graphical model and verification tool. This intermediary maintains a structured mapping between graphical model elements and verification scenarios, translating verification results back into the context of the original model. The test case database serves as an information hub that preserves contextual relationships, making verification results interpretable and actionable for model designers
Solution Approach 2:
The patent creates a universal test case framework that serves multiple functions: it stores verification scenarios, manages test data, tracks results, and provides contextual information linking back to the graphical model. This multi-functional system eliminates the need for separate configuration environments and languages, consolidating verification capabilities while maintaining seamless context alignment throughout the verification process
3Reliability
If multiple verification scenarios are executed to cover all possible input values, then verification thoroughness is improved, but resource consumption increases
Solution Approach 1:
The patent applies partial action by selectively executing verification scenarios based on priority and impact analysis. Instead of uniformly executing all possible verification scenarios, the system identifies and executes the most critical ones first, achieving sufficient verification thoroughness with reduced computational resources. The test case management system enables this by filtering and prioritizing scenarios based on predefined criteria such as risk level and functional importance
Solution Approach 2:
The patent implements dynamic verification resource allocation where the verification tool automatically adjusts the number and type of scenarios executed based on feedback from previous runs and the current state of the graphical model. This dynamic adaptation allows the system to allocate computational resources flexibly, executing comprehensive verification only when necessary and using lighter-weight verification methods when appropriate, thereby reducing overall resource consumption while maintaining thoroughness
Data Source
AI summary
Methods, mediums, and systems are presented herein for evaluating points of observation in a model by validating conditions in the model. A condition is a location in a model which may be either satisfied or unsatisfied by underlying data associated with the condition. Conditions may be placed in an enforced satisfied status or enforced unsatisfied status in order to instruct a verification tool to assume that the condition is satisfied regardless of whether the condition would actually be satisfied by underlying data. A first condition in an enforced satisfied status or an enforced unsatisfied status may be used to determine whether a second condition is satisfied, or whether a second condition satisfiable.