Dynamic Error Handling Database for Embedded Systems
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Solution Overview
Problem
Existing embedded computerized systems face challenges in efficiently handling device faults and events, requiring significant resources and time for error analysis and code preparation, especially due to the complexity of identifying and addressing hardware malfunctions.
Innovation Solution
A method that utilizes table-driven algorithms to simplify device fault and event handling by generating dynamically allocated and statically precompiled databases during runtime and prior to runtime, respectively, to systematically manage and recover from potential errors through pre-defined data structures and error handling tables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional error handling methods are used for device fault and event handling, then comprehensive error coverage can be achieved, but the amount of coding required increases significantly and development time is extended
Solution Approach 1:
The patent applies preliminary action by pre-defining error handling tables and data structures before runtime. The system pre-allocates memory structures and defines error handling protocols in advance, allowing the system to quickly respond to errors without requiring extensive coding for each possible error scenario. This reduces development time while maintaining comprehensive error coverage.
Solution Approach 2:
The patent changes parameters by transitioning from static, hard-coded error handling to dynamic, runtime-allocated error handling structures. The system uses configurable parameters and data structures that can be adjusted at runtime, allowing flexible error handling without requiring extensive recompilation or recoding. This enables comprehensive error coverage with reduced development effort.
2Reliability
If traditional error handling methods are used for device fault and event handling, then all potential errors can be addressed, but resource consumption increases due to extensive code analysis and preparation
Solution Approach 1:
The patent applies segmentation by dividing error handling into distinct, modular components. The system segments error handling into separate data structures and tables that can be independently managed and processed. This modular approach reduces computational overhead by allowing the system to process only relevant error segments rather than analyzing extensive code for all potential errors.
Solution Approach 2:
The patent uses copying by creating standardized error handling templates and data structures that can be replicated and reused. Instead of analyzing and preparing unique code for each error scenario, the system uses copyable error handling patterns and pre-defined data structures, significantly reducing computational resources required for error handling preparation.
3Difficulty of detecting and measuring
If complex error handling code is implemented, then detailed error analysis capability is improved, but the complexity of the system increases
Solution Approach 1:
The patent introduces an intermediary layer in the form of error handling tables and data structures that mediate between error detection and error response. Instead of complex code directly handling all error analysis, the system uses intermediate data structures to organize and manage error information, simplifying the overall system architecture while maintaining detailed error detection capability.
4Speed
If static precompiled databases are used for error handling, then error handling speed is improved, but adaptability to new devices added at runtime is reduced
Solution Approach 1:
The patent applies dynamics by combining static precompiled error handling tables with dynamic runtime allocation capabilities. The system maintains pre-defined error handling structures for speed while allowing dynamic addition of new devices and error scenarios at runtime. This dynamic approach enables both fast error handling and adaptability to new devices without requiring system recompilation.
Data Source
AI summary
A method identifies, prior to runtime, a first device that is added to a system. Further, the method generates, prior to runtime, a statically precompiled database for the device that provides a first set of error handling data. In addition, the method identifies, during runtime, a second device that is added to the system. Finally, the method generates, during runtime, a dynamically allocated database for the second device that provides a second set of error handling data.