Service Access Points for RTE Code Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems require users to manually schedule algorithmic code and modify models to accommodate Runtime Environment (RTE) specifications, leading to tedious, error-prone, and inefficient processes that render code unusable across different RTEs.
Innovation Solution
A processor analyzes an executable model to identify functionalities needing RTE services and model constraints, generating service access points based on deployment specifications, allowing code to be regenerated for different RTEs without modifying the model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually schedule algorithmic code and modify models to accommodate RTE specifications, then code can be adapted to specific RTE requirements, but the process becomes tedious, error-prone, and inefficient
Solution Approach 1:
The system performs self-service by automatically analyzing the executable model and generating service access points without requiring manual user intervention. The processor autonomously identifies functionalities needing RTE services and generates appropriate service access points based on deployment specifications, eliminating the tedious manual scheduling process while maintaining adaptability to different RTE requirements
Solution Approach 2:
The system changes parameters by generating service access points with different locations and characteristics based on deployment specifications. Instead of manually modifying code for each RTE, the system automatically adjusts parameters such as service access point location and configuration to match different RTE requirements, thereby improving productivity while maintaining adaptability
2Reliability
If users manually schedule algorithmic code and modify models to accommodate RTE specifications, then code can satisfy deployment specifications, but the process is error-prone
Solution Approach 1:
The system eliminates manual operations by performing self-service analysis of the executable model to identify functionalities needing RTE services. The processor automatically generates service access points without user intervention, removing the error-prone manual scheduling process while ensuring reliable compliance with deployment specifications through automated validation
Solution Approach 2:
The system incorporates feedback mechanisms where the processor analyzes the executable model and deployment specifications to generate appropriate service access points. This feedback loop ensures that generated code automatically complies with deployment specifications without requiring manual verification, thereby improving reliability while simplifying operation
3Adaptability or versatility
If code is generated for specific RTE requirements, then code can satisfy deployment specifications, but code cannot be reused across different RTEs
Solution Approach 1:
The system achieves universality by generating service access points that can be reused across different RTEs. The processor analyzes the executable model once and generates service access points that satisfy deployment specifications for multiple RTE platforms, enabling a single codebase to serve multiple RTE requirements without requiring separate code generation for each platform
Solution Approach 2:
The system segments the code generation process into two independent parts: the executable model (which remains unchanged and platform-independent) and the service access points (which are generated based on deployment specifications). This segmentation allows the model to be reused across different RTEs while the service access points are automatically adapted to match specific RTE requirements, thereby achieving both reusability and flexibility
4Manufacturing precision
If detailed low-level RTE specifications are provided, then code can be precisely generated for specific RTE requirements, but the need for such detailed specifications increases complexity
Solution Approach 1:
The system performs self-service analysis of the executable model to automatically identify functionalities needing RTE services and generate appropriate service access points. This eliminates the need for users to provide detailed low-level specifications, as the system autonomously determines the necessary precision by analyzing the model and generating code that satisfies deployment specifications without requiring complex user input
Data Source
Figure 1
Figure 2
Figure 3A
AI summary
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.